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Research summary: Most strategic management studies adopt an average-centered view that uses the central tendency to explain between-group variation in performance (i.e., performance differences between business units, firms, industries, and countries). In this study, we explain within-group variation using a variance-centered view that focuses on the peripheral characteristics of performance distributions as defined by skew and heavy tails (i.e., variance and kurtosis). Drawing on performance feedback theory, we hypothesize that successful firms tend to develop a positive skew in their performance distributions, which we call a \"positive skew effect\" in this study, and that heavy tails moderate this effect. Our analysis of the performance of a group of foreign affiliates provides general support for our hypotheses at both the firm and segment (industry and country) levels. Managerial summary: Managers of multi-business firms use various approaches to improve the aggregate performance of their business units. Some expand the range of upper performance outliers (exploration) or reduce the range of lower outliers (downsizing); others improve the performance of current business units (exploitation). We find that firms with superior performance tend to have a balanced mix of the three approaches. We also find that segments (countries and industries) with higher mean performances provide environments that facilitate the entry of productive firms and the exit of unproductive firms and provide environments in which incumbents can further improve their performance by learning from others. We observe that successful firms and segments have a positive skew in their performance distributions, which we call a \"positive skew effect.\"

[This corrects the article DOI: 10.3389/fimmu.2024.1452195.].

Climate change has increased the frequency and intensity of natural disasters. Does this translate into increased economic damages? To date, empirical assessments of damage trends have been inconclusive. Our study demonstrates a temporal increase in extreme damages, after controlling for a number of factors. We analyze event-level data using quantile regressions to capture patterns in the damage distribution (not just its mean) and find strong evidence of progressive rightward skewing and tail-fattening over time. While the effect of time on averages is hard to detect, effects on extreme damages are large, statistically significant, and growing with increasing percentiles. Our results are consistent with an upwardly curved, convex damage function, which is commonly assumed in climate-economics models. They are also robust to different specifications of control variables and time range considered and indicate that the risk of extreme damages has increased more in temperate areas than in tropical ones. We use simulations to show that underreporting bias in the data does not weaken our inferences; in fact, it may make them overly conservative.

Laser weld point detection is crucial in modern industrial manufacturing, yet it faces challenges such as a limited number of samples, uneven distribution, and diverse, irregular shapes. To address these issues, this paper proposes an innovative model, YOLO-Weld, which achieves lightweight design while enhancing detection accuracy. Firstly, a targeted data augmentation strategy is employed to increase both the quantity and diversity of samples from minority classes. Following this, a Diverse Class Normalization Loss (DCNLoss)function is designed to emphasize the importance of tail data in the model’s training. Secondly, the Adaptive Hierarchical Intersection over Union Loss (AHIoU Loss)function is introduced, which assigns varying levels of attention to different Intersections over Union (IoU) samples, with a particular focus on moderate IoU samples, thereby accelerating the bounding box regression process. Finally, a lightweight multi-scale feature processing module, MSBCSPELAN, is proposed to enhance multi-scale feature handling while reducing the number of model parameters. Experimental results indicate that YOLO-Weld significantly improves the accuracy and efficiency of laser weld point detection, with mean Average Precision at 50 ( ) and mean Average Precision at 50:95 ( ) increasing by 15.6% and 15.8%, respectively. Additionally, the model’s parameter count is reduced by 0.4 M, GFLOPS decreases by 1.1, precision improves by 4.3%, recall rises by 22.2%, and the F1 score increases by 15.1%.

We empirically examine the impact of expanded product variety on demand concentration using large data sets from the movie rental industry as our test bed. We find that product variety is likely to increase demand concentration, which goes against the “long tail effect” theory predicting that demand will become less concentrated on “hit” products because of expanded product variety. We further provide evidence that this finding is not due to introducing many low-selling niche products, as the intuition might suggest. Instead, we discover that increasing product variety diversifies the demand away from each movie title, but less significantly for hits than for niche products. In particular, we find that increasing product variety by 1,000 titles may increase the Gini coefficient of DVD rentals by 0.0029, which translates to increasing the market share of the top 1% of DVDs by 1.96% and the market share of the top 10% of DVDs by 0.58%. At the same time, the market share of the bottom 1% of DVDs is reduced by 21.29%, while the market share of the bottom 10% of DVDs is reduced by 5.28%. We rule out alternative explanations using a variety of long tail metrics, capturing movie format/distribution channel interaction and customer heterogeneity, while making use of instrumental variables.

Tail effect is a unique phenomenon in immunotherapy characterized by the prolonged maintenance of therapeutic efficacy. It can be observable even after treatment cessation. Immunotherapy has gradually become a vital regimen for the treatment of advanced lung cancer patients, among which immune-combined therapies based on immune checkpoint inhibitors (ICIs) have been applied clinically and demonstrates considerable clinical efficacy. In this case report, the patient was pathologically diagnosed with pulmonary sarcomatoid carcinoma (PSC), a rare and highly aggressive subtype of non-small cell lung cancer (NSCLC) known for its poor prognosis due to high invasiveness and metastatic potential. After developing resistance to chemotherapy, the patient was treated with a combined regimen of sintilimab and anlotinib, leading to initial clinical improvement. Following just three cycles of this regimen, treatment was discontinued, and the patient was discharged. Remarkably, over the subsequent months, the patient exhibited a significant tail effect, evidenced by sustained therapeutic stability, continuous tumor regression, stable low levels of serum carcinoembryonic antigen (CEA), and further improvement in clinical symptoms. Tail effect is a golden tail of immunotherapy. This case illustrates that the tail effect of immunotherapy can offer substantial survival benefits for patients with unresectable advanced lung cancer who have failed chemotherapy.

Xenopus laevis and tropicalis tadpoles display incredible regenerative capacity of their tail. Amaya and colleagues find that tadpole tail amputation induces the production of reactive oxygen species (ROS) to induce cell proliferation and regeneration, through activation of the Wnt/β-catenin and Fgf20 signalling pathways. Understanding the molecular mechanisms that promote successful tissue regeneration is critical for continued advancements in regenerative medicine. Vertebrate amphibian tadpoles of the species Xenopus laevis and Xenopus tropicalis have remarkable abilities to regenerate their tails following amputation 1 , 2 , through the coordinated activity of numerous growth factor signalling pathways, including the Wnt, Fgf, Bmp, Notch and TGF-β pathways 3 , 4 , 5 , 6 . Little is known, however, about the events that act upstream of these signalling pathways following injury. Here, we show that Xenopus tadpole tail amputation induces a sustained production of reactive oxygen species (ROS) during tail regeneration. Lowering ROS levels, using pharmacological or genetic approaches, reduces the level of cell proliferation and impairs tail regeneration. Genetic rescue experiments restored both ROS production and the initiation of the regenerative response. Sustained increased ROS levels are required for Wnt/β-catenin signalling and the activation of one of its main downstream targets, fgf20 (ref.  7 ), which, in turn, is essential for proper tail regeneration. These findings demonstrate that injury-induced ROS production is an important regulator of tissue regeneration.

The microchip-based electrochemical detection system (μEDS) has attracted plenty of research attention due to its merits including the capability in high-density integration, high sensitivity, fast analysis time, and reduced reagent consumption. The miniaturized working electrode is usually regarded as the core component of the μEDS, since its characteristic directly determines the performance of the whole system. Compared with the microelectrodes with conventional shapes such as the band, ring and disk, the three-dimensional (3D) micropillar array electrode (μAE) has demonstrated significant potential in improving the current response and decreasing the limits of detection due to its much larger reaction area. In this study, the numerical simulation method was used to investigate the performance of the μEDS, and both the geometrical and hydrodynamic parameters, including the micropillars shape, height, arrangement form and the flow rate of the reactant solution, were taken into consideration. The tail effect in μAEs was also quantitatively analyzed based on a pre-defined parameter of the current density ratio. In addition, a PDMS-based 3D μAE was fabricated and integrated into the microchannel for the electrochemical detection. The experiments of cyclic voltammetry (CV) and chronoamperometry (CA) were conducted, and a good agreement was found between the experimental and simulation results. This study would be instructive for the configuration and parameters design of the μEDS, and the presented method can be adopted to analyze and optimize the performance of nanochip-based electrochemical detection system (nEDS).

Many markets have traditionally been dominated by a few best-selling products, and this is also the case for the health care industry. However, we do not know whether the market will be more or less concentrated when health care services are delivered online (known as E-consultation), nor do we know how to reduce the concentration of the E-consultation market. The aim of this study was to investigate the concentration of the E-consultation market and how to reduce its concentration through information disclosure mechanisms (online reputation and self-representation). We employed a secondary data econometric analysis using transaction data obtained from an E-consultation Website (haodf.com) for three diseases (infantile pneumonia, diabetes, and pancreatic cancer) from 2008 to 2015. We included 2439 doctors in the analysis. The E-consultation market largely follows the 20/80 principle, namely that approximately 80% of orders are fulfilled by nearly 20% of doctors. This is much higher than the offline health care market. Meanwhile, the market served by doctors with strong online reputations (beta=0.207, P<.001) or strong online self-representation (beta=0.386, P<.001) is less concentrated. When health care services are delivered online, the market will be more concentrated (known as the \"Superstar\" effect), indicating poor service efficiency for society as a whole. To reduce market concentration, E-consultation websites should provide important design elements such as ratings of doctors (user feedback), articles contributed by doctors, and free consultation services (online representation). A possible and important way to reduce the market concentration of the E-consultation market is to accumulate enough highly rated or highly self-represented doctors.

New immunotherapy methods are being developed to provide cancer patients with survival benefit. The tail effect of immuno-oncology (IO) therapy resulting in diverse tails of survival curves between treatment arms may provide important information for physicians to guide treatment decisions in clinical practice. The hazard ratio (HR) and the log-rank test may not be suitable for quantifying and interpreting the between-group difference in IO clinical trials because the underlying assumption that the HR is constant over time is not valid. As an alternative summary measure, the restricted mean survival time (RMST) has been attracting more attention for comparing survival curves. The RMST is defined as the mean survival time to a specific threshold timepoint τ and is calculated as the area under the curve within a specific time window from 0 to τ. Although physicians may wish to compare the RMST up to the end timepoint of a longer curve to elucidate the tail effect of the IO treatment, with the currently available statistical methods, τ is required to be set at the end timepoint of a shorter curve or before. To address this issue, we propose a sensitivity analysis approach to evaluating the between-group difference in the RMST at any timepoint that clinical investigators consider clinically relevant, thus being free from such a statistical constraint. Notably, this analysis can only provide complementary results; thus, it cannot function as the primary analysis.