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Using a sample of (448.1±2.9)×106 𝜓(3686) decays collected with the BESIII detector at BEPCII, we report an observation of Ξ− transverse polarization with a significance of 7.3𝜎 in the decay 𝜓(3686)→Ξ− ¯Ξ+ (Ξ−→Λ𝜋−, ¯Ξ+→¯Λ𝜋+, Λ→𝑝𝜋−, ¯Λ→¯𝑝𝜋+). The relative phase of the electric and magnetic form factors is determined to be ΔΦ=(0.667±0.111±0.058) rad. This is the first measurement of the relative phase for a 𝜓(3686) decay into a pair of Ξ−¯Ξ+ hyperons. The Ξ− decay parameters (𝛼Ξ−, 𝜙Ξ−) and their conjugates (𝛼¯Ξ+, 𝜙¯Ξ+), the angular-distribution parameter 𝛼𝜓, and the strong-phase difference 𝛿𝑝−𝛿𝑠 for Λ𝜋− scattering are measured to be consistent with previous BESIII results.
Luminosities and energies of e⁺e⁻ collision data taken between √s=4.61 GeV and 4.95 GeV at BESIII
(2022)
From December 2019 to June 2021, the BESIII experiment collected about 5.85 fb−1 of data at center-of-mass energies between 4.61 GeV and 4.95 GeV. This is the highest collision energy BEPCII has reached so far. The accumulated e+e− annihilation data samples are useful for studying charmonium(-like) states and charmed-hadron decays. By adopting a novel method of analyzing the production of Λ+cΛ¯−c pairs in e+e− annihilation, the center-of-mass energies are measured with a precision of ∼0.6 MeV. Integrated luminosities are measured with a precision of better than 1\% by analyzing the events of large-angle Bhabha scattering. These measurements provide important inputs to the analyses based on these data samples.
A common element of market structure analysis is the spatial representation of firms’ competitive positions on maps. Such maps typically capture static snapshots in time. Yet, competitive positions tend to change. Embedded in such changes are firms’ trajectories, that is, the series of changes in firms’ positions over time relative to all other firms in a market. Identifying these trajectories contributes to market structure analysis by providing a forward-looking perspective on competition, revealing firms’ (re)positioning strategies and indicating strategy effectiveness. To unlock these insights, we propose EvoMap, a novel dynamic mapping framework that identifies firms’ trajectories from high-frequency and potentially noisy data. We validate EvoMap via extensive simulations and apply it empirically to study the trajectories of more than 1,000 publicly listed firms over 20 years. We find substantial changes in several firms’ positioning strategies, including Apple, Walmart, and Capital One. Because EvoMap accommodates a wide range of mapping methods, analysts can easily apply it in other empirical settings and to data from various sources.
Regulators worldwide have been implementing different privacy laws. They vary in their impact on the value for advertisers, publishers and users, but not much is known about these differences. This article focuses on three important privacy laws (i.e., General Data Protection Regulation [GDPR], California Consumer Privacy Act [CCPA] and Personal Information Protection Law [PIPL]) and compares their impact on the value for the three primary actors of the online advertising market, namely, advertisers, publishers and users. This article first compares these three privacy laws by developing a legal strictness score. It then uses the existing literature to derive the effects of the legal strictness of each privacy law on each actor’s value. Finally, it quantifies the three privacy laws’ impact on each actor’s value. The results show that GDPR and PIPL are similar and stricter than CCPA. Stricter privacy laws bring larger negative changes to the value for actors. As a result, both GDPR and PIPL decrease the actors’ value more substantially than CCPA. These value declines are the largest for publishers and are rather similar for users and advertisers. Scholars and practitioners can use our findings to explore ways to create value for multiple actors under various privacy laws.
For many services, consumers can choose among a range of optional tariffs that differ in their access and usage prices. Recent studies indicate that tariff-specific preferences may lead consumers to choose a tariff that does not minimize their expected billing rate. This study analyzes how tariff-specific preferences influence the responsiveness of consumers’ usage and tariff choice to changes in price. We show that consumer heterogeneity in tariff-specific preferences leads to heterogeneity in their sensitivity to price changes. Specifically, consumers with tariff-specific preferences are less sensitive to price increases of their preferred tariff than other consumers. Our results provide an additional reason why firms should offer multiple tariffs rather than a uniform nonlinear pricing plan to extract maximum consumer surplus.
Digitale Technologien begünstigen den Einsatz einer dynamischen Preisgestaltung, also von Preisen, die für ein prinzipiell gleiches Produkt unangekündigt variieren. Dabei werden in der öffentlichen Diskussion unterschiedliche Ausgestaltungsformen dynamischer Preise oftmals vermischt, was eine sinnvolle Analyse der Vor- und Nachteile der dynamischen Preisgestaltung erschwert. Das Ziel des Beitrags ist die Darstellung der ökonomischen Grundlagen und die Diskussion sowie Klassifikation der Ausgestaltungsmöglichkeiten der dynamischen Preisgestaltung. Darüber hinaus erfolgt eine Bewertung der Vor- und Nachteile der dynamischen Preisgestaltung aus Käufer- und Verkäufersicht. Abschließend werden Implikationen für die betriebswirtschaftliche Forschung diskutiert.
Thought to be monotypic for decades, the only species in the goosefish genus Lophiomus Gill, Lm. setigerus (Vahl), shows a wide range of morphological variation and is distributed widely in the Indo-West Pacific (IWP). In this study, datasets for two mitochondrial and two nuclear genes sequences obtained from samples of Lophiomus collected in different localities across the IWP were constructed and analyzed to explore the phylogeny and species diversity within the genus. Our integrated approach with multiline evidence unveiled an unanticipated richness of at least six delimited species of Lophiomus. Herein, based on materials already available from museums and new specimens obtained primarily through the Tropical Deep-Sea Benthos program surveying IWP benthic fauna, we formally describe three new species: Lm. immaculioralis sp. nov., Lm. nigriventris sp. nov., and Lm. carusoi sp. nov. Also, we resurrect Lm. laticeps stat. rev. from synonyms of Lm. setigerus. These species can be diagnosed by genetics, body coloration, patterns on the floor of the mouth, peritoneum pigmentation, morphometric measurements, and meristic counts of cranial spines, dorsal-fin spines, and pectoral-fin and pelvic-fin rays from each other and from Lm. setigerus. The species Lm. setigerus, as well as the genus Lophiomus, are re-described accordingly based on the new results. Amended identification keys to the four extant lophiid genera and to species of Lophiomus are also provided.
Background: Prostate cancer is a major health concern in aging men. Paralleling an aging society, prostate cancer prevalence increases emphasizing the need for efcient diagnostic algorithms.
Methods: Retrospectively, 106 prostate tissue samples from 48 patients (mean age,
66 ± 6.6 years) were included in the study. Patients sufered from prostate cancer (n = 38) or benign prostatic hyperplasia (n = 10) and were treated with radical prostatectomy or Holmium laser enucleation of the prostate, respectively. We constructed tissue microarrays (TMAs) comprising representative malignant (n = 38) and benign (n = 68) tissue cores. TMAs were processed to histological slides, stained, digitized and assessed for the applicability of machine learning strategies and open–source tools in diagnosis of prostate cancer. We applied the software QuPath to extract features for shape, stain intensity, and texture of TMA cores for three stainings, H&E, ERG, and PIN-4. Three machine learning algorithms, neural network (NN), support vector machines (SVM), and random forest (RF), were trained and cross-validated with 100 Monte Carlo random splits into 70% training set and 30% test set. We determined AUC values for single color channels, with and without optimization of hyperparameters by exhaustive grid search. We applied recursive feature elimination to feature sets of multiple color transforms.
Results: Mean AUC was above 0.80. PIN-4 stainings yielded higher AUC than H&E and
ERG. For PIN-4 with the color transform saturation, NN, RF, and SVM revealed AUC of 0.93 ± 0.04, 0.91 ± 0.06, and 0.92 ± 0.05, respectively. Optimization of hyperparameters improved the AUC only slightly by 0.01. For H&E, feature selection resulted in no increase of AUC but to an increase of 0.02–0.06 for ERG and PIN-4.
Conclusions: Automated pipelines may be able to discriminate with high accuracy between malignant and benign tissue. We found PIN-4 staining best suited for classifcation. Further bioinformatic analysis of larger data sets would be crucial to evaluate the reliability of automated classifcation methods for clinical practice and to evaluate potential discrimination of aggressiveness of cancer to pave the way to automatic precision medicine.
Climate change affects ecosystems worldwide and is threatening biodiversity. Insects, as ectotherm organisms, are strongly dependent on the thermal environment. Yet, little is known about the effects of summer heat and drought on insect diversity. In the Mediterranean climate zone, a region strongly affected by climate change, hot summers might have severe effects on insect communities. Especially the larval stage might be sensitive to thermal variation, as larvae—compared to other life stages—cannot avoid hot temperatures and drought by dormancy. Here we ask, whether inter-annual fluctuations in Mediterranean moth diversity can be explained by temperature (TLarv) and precipitation during larval development (HLarv). To address our question, we analyzed moth communities of a Mediterranean coastal forest during the last 20 years. For species with summer-developing larvae, species richness was significantly negatively correlated with TLarv, while the community composition was affected by both, TLarv and HLarv. Therefore, summer-developing larvae seem particularly sensitive to climate change, as hot summers might exceed the larval temperature optima and drought reduces food plant quality. Increasing frequency and severity of temperature and drought extremes due to climate change, therefore, might amplify insect decline in the future.