The digital transformation of Chinese companies offers a new frontier for organizational research. Widespread use of workplace platforms creates rich archives of unobtrusive data, providing continuous, real-time insights into organizational life that traditional surveys cannot capture. The central challenge for scholars is turning this data abundance into meaningful theory. This special issue highlights three studies that meet this challenge by using innovative methods to convert granular data into valuable knowledge. The papers employ digital-context experiments, real-time behavioral tracking, and machine-learning-assisted theory building to study phenomena from interpersonal dynamics to crisis productivity. Looking ahead, we explore the potential of unstructured multimodal data and new AI tools to make complex analysis more accessible. We conclude with a research agenda calling for methodological rigor, interdisciplinary collaboration, and a firm balance between technological innovation and theoretical depth.

The propagation of detonations in a non-uniform mixture exhibits notable distinctions from that in a uniform mixture. This study first delves into the analytical analysis of the one-dimensional shock transmission problem and the two-dimensional shock propagation in a mixture with temperature non-uniformity. Additionally, the research extends to the numerical simulation of the propagation of shocks and detonations, building upon the insights garnered from the analytical analysis. The numerical results indicate that introducing a temperature interface in a non-uniform gas creates a discrete flow field and wavefront, resulting in oblique shocks that connect hot and cold layers. A competitive mechanism between the transverse waves and non-uniformity is responsible for the detonation propagation. The temperature amplitude tends to inhibit the propagation of transverse waves. In contrast, the wavelengths primarily affect the spacing and strength of these transverse waves, especially during the early stages of propagation. In a Zel’Dovich–von Neumann–Döring detonation, the non-uniformities distort the detonation front, creating transverse wave spacings comparable to the wavelength and reducing the front velocity. However, the detonation can recover its Chapman–Jouguet velocity and approach a steady states as intrinsic instabilities come into play. In the steady state, the cell sizes are found to be determined by the temperature amplitude. When the temperature amplitude is sufficiently high, the detonation cells effectively disappear.

In the realm of data-to-text generation tasks, the use of large language models (LLMs) has become common practice, yielding fluent and coherent outputs. Existing literature highlights that the quality of in-context examples significantly influences the empirical performance of these models, making the efficient selection of high-quality examples crucial. We hypothesize that the quality of these examples is primarily determined by two properties: their similarity to the input data and their diversity from one another. Based on this insight, we introduce a novel approach, Double Clustering-based In-Context Example Selection, specifically designed for data-to-text generation tasks. Our method involves two distinct clustering stages. The first stage aims to maximize the similarity between the in-context examples and the input data. The second stage ensures diversity among the selected in-context examples. Additionally, we have developed a batched generation method to enhance the token usage efficiency of LLMs. Experimental results demonstrate that, compared to traditional methods of selecting in-context learning samples, our approach significantly improves both time efficiency and token utilization while maintaining accuracy.

This paper studies a distributed fixed-time dynamic event-triggered formation control framework for a group of hypersonic gliding vehicles (GHGVs) suffering from internal uncertainties and non-affine properties. The main challenge is strong coupling of non-affine nonlinear dynamic with hypervelocity characteristics and multi-source uncertainties make it difficult to design the control protocol. Firstly, by integrating the distributed consensus control strategy, fractional order control theory and dynamic event-triggered mechanism, a framework of fixed-time formation control for GHGVs system is constructed. Secondly, to mitigate the issue of ‘explosion of complexity’ (EI), a fixed-time command filter (FCF) is proposed and a compensative strategy is formulated to tackle the impact of filtering errors. Thirdly, an additional auxiliary differential equation (ADE) is developed to decouple the control input from the status variable. Several radial base function neural networks (RBFNN) are utilised to handle the unknown internal uncertainties. Furthermore, a unique dynamic event-triggered mechanism (DTEM) is introduced for each follower, facilitating seamless transitions between two distinct dynamic threshold strategies. Analysis based on Lyapunov function illustrates that the output tracking error of followers exponentially converges to a small range within a fixed time, and Zeno behaviour is prevented. Finally, several numerical simulations are presented to demonstrate the practicability and meliority of the suggested approach.

This paper studies the adaptive distributed consensus tracking control framework for hypersonic gliding vehicles (HGVs) flying in tight formation. The system investigated in this paper is non-affine and subjected to multisource disturbances and mismatched uncertainties caused by a dramatically changing environment. Firstly, by refining the primary factors in the three-dimensional cluster dynamics, a non-affine closed-loop control system is summarised. Note that actual control is coupled with states, an additional auxiliary differential equation is developed to introduce additional affine control inputs. Furthermore, by employing the hyperbolic tangent function and disturbance boundary estimator, time-varying multisource disturbances can be handled. Several radial base function neural networks (RBFNNs) are utilised to approximate unknown nonlinearities. Furthermore, a generalised equatorial coordinate system is proposed to convert the longitudinal, lateral and vertical relative distances in the desired formation configuration into first-order consensus tracking error, such as latitude, longitude and height deviations. Analysis based on the Lyapunov function illustrates that variables are globally uniformly bounded, and the output tracking error of followers exponentially converges to a small neighbourhood. Finally, numerical simulations of equilibrium glide and spiral diving manoeuvers are provided to demonstrate the validity and practicability of the proposed approach.

Persistent malnutrition is associated with poor clinical outcomes in cancer. However, assessing its reversibility can be challenging. The present study aimed to utilise machine learning (ML) to predict reversible malnutrition (RM) in patients with cancer. A multicentre cohort study including hospitalised oncology patients. Malnutrition was diagnosed using an international consensus. RM was defined as a positive diagnosis of malnutrition upon patient admission which turned negative one month later. Time-series data on body weight and skeletal muscle were modelled using a long short-term memory architecture to predict RM. The model was named as WAL-net, and its performance, explainability, clinical relevance and generalisability were evaluated. We investigated 4254 patients with cancer-associated malnutrition (discovery set = 2977, test set = 1277). There were 2783 men and 1471 women (median age = 61 years). RM was identified in 754 (17·7 %) patients. RM/non-RM groups showed distinct patterns of weight and muscle dynamics, and RM was negatively correlated to the progressive stages of cancer cachexia (r = –0·340, P < 0·001). WAL-net was the state-of-the-art model among all ML algorithms evaluated, demonstrating favourable performance to predict RM in the test set (AUC = 0·924, 95 % CI = 0·904, 0·944) and an external validation set (n 798, AUC = 0·909, 95 % CI = 0·876, 0·943). Model-predicted RM using baseline information was associated with lower future risks of underweight, sarcopenia, performance status decline and progression of malnutrition (all P < 0·05). This study presents an explainable deep learning model, the WAL-net, for early identification of RM in patients with cancer. These findings might help the management of cancer-associated malnutrition to optimise patient outcomes in multidisciplinary cancer care.

Mapping reviews (MRs) are crucial for identifying research gaps and enhancing evidence utilization. Despite their increasing use in health and social sciences, inconsistencies persist in both their conceptualization and reporting. This study aims to clarify the conceptual framework and gather reporting items from existing guidance and methodological studies. A comprehensive search was conducted across nine databases and 11 institutional websites, including documents up to January 2024. A total of 68 documents were included, addressing 24 MR terms and 55 definitions, with 39 documents discussing distinctions and overlaps among these terms. From the documents included, 28 reporting items were identified, covering all the steps of the process. Seven documents mentioned reporting on the title, four on the abstract, and 14 on the background. Ten methods-related items appeared in 56 documents, with the median number of documents supporting each item being 34 (interquartile range [IQR]: 27, 39). Four results-related items were mentioned in 18 documents (median: 14.5, IQR: 11.5, 16), and four discussion-related items appeared in 25 documents (median: 5.5, IQR: 3, 13). There was very little guidance about reporting conclusions, acknowledgments, author contributions, declarations of interest, and funding sources. This study proposes a draft 28-item reporting checklist for MRs and has identified terminologies and concepts used to describe MRs. These findings will first be used to inform a Delphi consensus process to develop reporting guidelines for MRs. Additionally, the checklist and definitions could be used to guide researchers in reporting high-quality MRs.

This study evaluated the effects of chenodeoxycholic acid (CDCA), a farnesoid X receptor (FXR) potential activator, on growth performance, antioxidant capacity, glucose metabolism and inflammation in largemouth bass (Micropterus salmoides) (initial body weight: 5·45 ± 0·02 g) fed a high-carbohydrate diet. Experimental diets included a positive control (5 % α-starch), a negative control (10 % α-starch) and two diets containing 10 % α-starch supplemented with either 0·05 % or 0·10 % CDCA. After 8 weeks, the high-carbohydrate diet reduced growth performance and increased hepatosomatic and viscerosomatic indexes, which were mitigated by 0·10 % CDCA supplementation. The high-carbohydrate diet also increased hepatic glycogen and crude lipid content, both of which were reduced by 0·10 % CDCA. Furthermore, the high-carbohydrate diet-induced oxidative stress, histopathological changes and reduced liver lysozyme activity, which were ameliorated by CDCA supplementation. Molecular analysis showed that the high-carbohydrate diet suppressed FXR and phosphorylated AKT1 (p-AKT1) protein expression in the liver, downregulated insulin signalling (ira, irs, pi3kr1 and akt1), gluconeogenesis (pepck and g6pc) and glycolysis genes (gk, pk and pfkl). CDCA supplementation upregulated fxr expression, activated shp, enhanced the expression of insulin signalling and glycolytic genes (gk, pk and pfkl) and inhibited gluconeogenesis. Additionally, CDCA reduced inflammatory markers (nf-κb and il-1β) and restored anti-inflammatory mediators (il-10, iκb and tgf-β). In conclusion, 0·10 % CDCA improved carbohydrate metabolism and alleviated liver inflammation in largemouth bass fed a high dietary carbohydrate, partially through FXR activation.

This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.

The Mamyshev oscillator (MO) is well-known for its high modulation depth, which provides an excellent platform for achieving both high average power and short pulse durations. However, this characteristic typically limits the high-repetition-rate pulse generation. Herein, we construct an MO that achieves a gigahertz (GHz) repetition rate through harmonic mode-locking. The laser can reach up to the 93rd order, which corresponds to the repetition rate of 1.6 GHz. The maximum achieved output average power is 3 W at a repetition rate of 1.2 GHz (69th order), with the corresponding pulse duration compressed to 51 fs. To our knowledge, this is the first time that the GHz repetition rate in an MO has been obtained simultaneously with the recorded average power and pulse duration.

The Early-Middle Jurassic impression/compression macroflora and the palynoflora from the Qaidam Basin in the northeastern Qinghai-Xizang (Tibetan) Plateau have been well studied; however, fossil wood from this region has not been previously documented systematically. Here, we describe an anatomically well-preserved fossil wood specimen from the Lower Jurassic Huoshaoshan Formation at the Dameigou section in northern Qinghai Province, northwestern China. This fossil exhibits typical Metapodocarpoxylon Dupéron-Laudoueneix et Pons anatomy with usually araucarian radial tracheid pits and variable cross-field pits, representing a new record for Metapodocarpoxylon in the Qaidam Basin. This discovery indicates that trees with this type of wood anatomy were not confined to northern Gondwana but also grew in more northerly regions in Laurasia. The wood displays distinct growth rings, with abundant, well-formed earlywood and narrow latewood. This observation, along with previous interpretations based on macroflora, palynoflora and sedimentological data, suggests that a warm and humid climate with mild seasonality prevailed in the region during the Early Jurassic.

Bronze mou vessels appear in Shu tombs in south-west China during the Eastern Zhou period (c. 771–256 BC). Examination of these vessels reveals major changes in the supply of metal and alloying technology in the Shu State, throwing new light on the social impact of the Qin conquest and later unification of China.

Let X be a compact Kähler manifold, and let $L \rightarrow X$ be a holomorphic line bundle equipped with a singular metric h such that the curvature $\mathrm {i}\Theta _{L,h}\geqslant 0$ in the sense of currents. The main result of this paper is the vanishing of $H^n(X,\mathcal {O}(\Omega ^p_X\otimes L)\otimes \mathcal {I}(h))$ for $p\geqslant n-\operatorname {nd}(L,h)+1$, which generalizes Bogomolov’s vanishing theorem and Watanabe’s result.

This paper introduces a novel fiber-based picosecond burst-mode laser system capable of operating at high power and high repetition rates. A pulse-circulating fiber ring was developed as a burst generator, achieving an intra-burst repetition rate of 469 MHz without the need for a high-repetition-rate seed source. This design also allows for flexible adjustment of the number of sub-pulses, burst repetition rate and burst shape. In addition, a master oscillator power amplifier was employed to analyze the amplification characteristics of bursts. The system demonstrated a maximum average power of 606 W, with a measured sub-pulse duration of 62 ps and the highest sub-pulse peak power of 980 kW. To the best of our knowledge, this marks the highest average power obtained in burst-mode ultrafast lasers. Such a laser system holds potential for applications in precision manufacturing, high-speed imaging, high-precision ranging and other diverse domains.