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We present an efficient MPI-parallel algorithm and its implementation for evaluating the self-consistent correlated second-order exchange term (SOX), which is employed as a correction to the fully self-consistent GW scheme called scGWSOX (GW plus the SOX term iterated to achieve full Green's function self-consistency). Due to the application of the tensor hypercontraction (THC) in our computational procedure, the scaling of the evaluation of scGWSOX is reduced from O ( n τ n A O 5 ) to O ( n τ N 2 n A O 2 ). This fully MPI-parallel and THC-adapted approach enabled us to conduct the largest fully self-consistent scGWSOX calculations with over 1100 atomic orbitals with only negligible errors attributed to THC fitting. Utilizing our THC implementation for scGW, scGF2, and scGWSOX, we evaluated energies of intermolecular interactions. This approach allowed us to circumvent issues related to reference dependence and ambiguity in energy evaluation, which are common challenges in non-self-consistent calculations. We demonstrate that scGW exhibits a slight overbinding tendency for large systems, contrary to the underbinding observed with non-self-consistent RPA. Conversely, scGWSOX exhibits a slight underbinding tendency for such systems. This behavior is both physical and systematic and is caused by exclusion-principle violating diagrams or corresponding corrections. Our analysis elucidates the role played by these different diagrams, which is crucial for the construction of rigorous, accurate, and systematic methods. Finally, we explicitly show that all perturbative fully self-consistent Green's function methods are size-extensive and size-consistent. [ABSTRACT FROM AUTHOR]

Theories of small systems play an important role in the fundamental understanding of finite size effects in statistical mechanics, as well as the validation of molecular simulation results as no computer can simulate fluids in the thermodynamic limit. Previously, a shell particle was included in the isothermal–isobaric ensemble in order to resolve an ambiguity in the resulting partition function. The shell particle removed either redundant volume states or redundant translational degrees of freedom of the system and yielded quantitative differences from traditional simulations in this ensemble. In this work, we investigate the effect of including a shell particle in the canonical, grand canonical, and Gibbs ensembles. For systems comprised of a pure component ideal gas, analytical expressions for various thermodynamic properties are obtained. We also derive the Metropolis Monte Carlo simulation acceptance criteria for these ensembles with shell particles, and the results of the simulations of an ideal gas are in excellent agreement with the theoretical predictions. The system size dependence of various important ensemble averages is also analyzed. [ABSTRACT FROM AUTHOR]

Bricolage – a term that implies resourcefulness – is a construct with a long history in anthropology, design, management, and entrepreneurship, among other fields. Our study is one of the first to apply the bricolage concept to better understand the behaviors of salespeople. Overall, findings from our multi-study, multi-method approach (combining survey methodology and a scenario-based experiment with video manipulations) indicate that salesperson bricolage behaviors are desirable and can be developed in a sales force. More specifically, in Study 1, we leverage Job Demands-Resources Theory and survey data from 405 business-to-business (B2B) salespeople and find that salesperson bricolage behaviors can effectively mitigate the predictably negative impacts of role ambiguity on sales performance. In Study 2, we leverage Self-Determination Theory and an experimental design with 181 B2B salespeople and provide initial evidence regarding salesperson bricolage behaviors' organizational determinants (i.e. sales force control system combinations). Study 2 indicates that capability control interacted synergistically with outcome control and antagonistically with activity control in predicting bricolage behaviors. Taken together, findings from the two studies indicate that bricolage behaviors are both beneficial and manageable, warranting continued study in the sales literature. [ABSTRACT FROM AUTHOR]

Estate planning is a multifaceted process encompassing the accumulation, management, and preservation of wealth. Among estate planning tools like wills or life insurance policies, two common options for asset distributions are per stirpes and per capita. Per stirpes distribution, which is relatively straightforward and more widely used, directs the inheritance to the lineal descendants of a predeceased beneficiary. In contrast, the per capita method has varying interpretations in estate planning, financial planning, and insurance fields. This method encompasses several options. This article delves into the ambiguities in the per capita option, particularly the lack of a standardized definition. It underscores the necessity for financial professionals to navigate these distinctions effectively, ensuring clients' objectives are met precisely and clearly in a field where precision and clarity are paramount. [ABSTRACT FROM AUTHOR]

New entrants and incumbent firms rely on new knowledge to innovate and compete in the market. One way to acquire new knowledge is through the recruitment of new employees from competitors, a phenomenon popularly known as "poaching." Digital labor platforms are widely used by firms for this aim. We argue that job titles represent the first and most visible public source of information about knowledge workers and thus play a key role in navigating the vast spectrum of competencies available in digital platforms. Our analyses of the career trajectories of 11,644 knowledge workers in the United States between 2004 and 2014 suggest that increases in the ambiguity of a job title claimed by an employee are negatively associated with the likelihood of the employee being hired by a new employer. This finding appears stronger in the case of transitions to incumbent firms rather than new entrants. In the concluding section of the paper, we take stock of the various analyses presented and reflect on the potential role of job titles in the strategic management of human capital. [ABSTRACT FROM AUTHOR]

This paper studies the supplier selection and order allocation (SS&OA) problem, where risks include a series of disruption scenarios with uncertain probability of occurrence. It is a challenge for industry decision-makers to balance the average cost and the level of risk under the ambiguity set for probabilities. To address this challenge, a two-stage distributionally robust (DR) Mean-CVaR model is presented for the SS&OA problem. A procedure is developed for constructing the ambiguity set, and Polyhedral and Box ambiguity sets are constructed to characterise the uncertain probabilities. The worst-case Mean-CVaR criterion is employed for the second-stage cost within the ambiguity set to trade off the expected cost and CVaR value. Three measures are incorporated to increase the resilience of the supply chain. The proposed robust model is reformulated into two mixed-integer linear programming models. A real case of the Huawei cell phone manufacturer is used to illustrate the validity of the proposed approach in numerical settings. Experimental results show that the new optimising approach can provide a robust SS&OA solution to immunise against the influence caused by uncertain probabilities. By comparative analyses, some management insights are obtained for industry decision-makers. [ABSTRACT FROM AUTHOR]

Since the full system deployment of BDS-3 in July 2020, it has provided stable and reliable positioning, navigation and timing (PNT) services for users around the world. It is an urgent task to explore the potential performance of precise point positioning (PPP) based on the full constellation of BDS-2/BDS-3. This research presented the global satellite visibility of BDS-2/BDS-3, analyzed the stability and accuracy of BDS-2 and BDS-3 rubidium clocks and hydrogen clocks, jointly estimated the BDS-2 and BDS-3 fractional cycle biases (FCB) and evaluated the PPP performance with ambiguity resolution (AR). Due to the fact that International GNSS Service (IGS) precise products have a great impact on narrow-lane (NL) FCB estimation, the FCB obtained by using the precise products from CODE (Center for Orbit Determination in Europe) and GBM (Deutsches GeoForschungsZentrum) in two different analysis centers and the FCB obtained by using GBM precise products with different calculation strategies are analyzed. In addition, the experimental data from Multi-GNSS Experiment (MGEX), EUREF (EPN) and Germany (GPN) observation networks are used to evaluate the influence of orbital errors on BDS FCB estimation. For wide-lane (WL) FCB, MGEX WL FCB has the highest accuracy, followed by EPN and GPN. On the contrary, for NL FCB, MGEX NL FCB has the worst accuracy, followed by EPN, and GPN is the best. Eventually, numerous experiment results showed that compared with the static float solution, the PPP fixed solutions in East (E), North (N) and Up (U) directions are improved by 32.9%, 27.7%, 13.8% for BDS-3 and 10.0%, 7.5%, 3.8% for BDS-2/BDS-3. Compared with the kinematic float solution, the PPP fixed solutions in E, N and U directions are improved by 27.9%, 23.4%, 16.6% for BDS-3 and 15.9%, 8.9%, 5.3% for BDS-2/BDS-3. [ABSTRACT FROM AUTHOR]

By clustering multiple microgrids (MGs), a multi-microgrid (MMG) system plays a significant role in integrating a large amount of renewable generation. However, the large-scale utilization of renewable energy also brings uncertainties to MMG energy management. In this work, a novel comprehensive bi-level MMG energy management model considering uncertainties of renewable energy is first developed which includes unit commitment (UC) problem and other models in the lower MG level. Then considering the non-convexity of the bi-level problem, a decomposition method called analytical target cascading (ATC) is employed to deal with it by decentralization. With regard to the energy management of each individual MG, a two-stage distributionally robust model is developed which describes the uncertainties from probability distribution of renewable generation with a metric-based ambiguity set. Moreover, an efficient solution scheme based on column and constraint generation (CCG) algorithm and a decomposition method without duality is designed to handle the MG energy management problem. Finally, we implement extensive experiments to corroborate the effectiveness of the proposed approach. Particularly, the optimal solution from the proposed method can attain 2.98% less cost compared with that from robust optimization (RO) method and achieve 86.17% less energy trading amount than that in independent mode. [ABSTRACT FROM AUTHOR]

In this paper, we present an innovative framework for 2D-to-3D human pose estimation from video, harnessing the power of multi-scale multi-level spatial-temporal features. Our framework comprises three integral branch networks: A temporal feature core network, dedicated to extracting temporal coherence among frames, enabling a comprehensive understanding of dynamic human motion. A multi-scale feature branch network, equipped with multiple receptive fields of varying sizes, facilitating the extraction of multi-scale features, thus capturing fine-grained details across different scales. A multi-level feature branch network, tasked with extracting features from layers at various depths within the architecture, providing a nuanced understanding of pose-related information. Within our framework, these diverse features are seamlessly integrated to encapsulate intricate spatial and temporal relationships inherent to the human body. This integration effectively addresses challenges such as depth ambiguity and self-occlusions, culminating in substantially improved accuracy in pose estimation.Extensive experiments on Human3.6M and HumanEva-I show that our framework achieves competitive performance on 2D-to-3D human pose estimation in video. Code is available at: https://github.com/fll123/3Dhumanpose. [ABSTRACT FROM AUTHOR]

A mathematical tool used to analyze signals in high-dimensional areas is the biquaternion ambiguity function. While typical ambiguity functions deal with time delay and Doppler frequency, biquaternion ambiguity functions extend the concept to rotations and scaling factors. Biquaternion ambiguity functions offer a more thorough representation of signal ambiguity in these high-dimensional spaces, which can help develop better signal processing algorithms for a range of uses. In this paper, we introduce the notion of biquaternion ambiguity function which is formed from conventional ambiguity function by invoking biquaternion algebra. We first establish the various properties, namely dilation, translation, shift, nonlinearity, boundedness, reconstruction formula, Moyal’s formula, and inversion formula. An interesting relationship between the biquaternion Fourier transform and the biquaternion ambiguity function is also established. Furthermore, we establish the various versions of uncertainty inequalities namely, Pitt’s inequality, sharp Hausdorff–Young inequality, sharp Local uncertainty principle and logarithmic uncertainty principle for biquaternion ambiguity function. Some potential applications are also presented at the end. [ABSTRACT FROM AUTHOR]

In the later seventeenth century, a path passing through the Temple Newsam estate in West Yorkshire became the subject of intense and prolonged litigation. The disputants contested whether the path was for the privileged use of the owners and tenants of Temple Newsam or was in fact a common highway. Using the records of this unusually well-recorded dispute, this essay explores how personal memory, exemplified by the testimony of four witnesses accused of perjury, could be used to challenge customary memory in determining the ‘truth’ of such recollections of the landscape. This analysis refines scholarly approaches to memory in legal disputes. It emphasizes the personal characteristics that could influence witness memory, such as age and time, as well as the ambiguity between misremembering and forgetting. This article further argues that long-standing but non-customary practices related to the landscape needed to be remembered and maintained as much as customary practices. [ABSTRACT FROM AUTHOR]

Many individually randomized group treatment (IRGT) trials randomly assign individuals to study arms but deliver treatments via shared agents, such as therapists, surgeons, or trainers. Post‐randomization interactions induce correlations in outcome measures between participants sharing the same agent. Agents can be nested in or crossed with trial arm, and participants may interact with a single agent or with multiple agents. These complications have led to ambiguity in choice of models but there have been no systematic efforts to identify appropriate analytic models for these study designs. To address this gap, we undertook a simulation study to examine the performance of candidate analytic models in the presence of complex clustering arising from multiple membership, single membership, and single agent settings, in both nested and crossed designs and for a continuous outcome. With nested designs, substantial type I error rate inflation was observed when analytic models did not account for multiple membership and when analytic model weights characterizing the association with multiple agents did not match the data generating mechanism. Conversely, analytic models for crossed designs generally maintained nominal type I error rates unless there was notable imbalance in the number of participants that interact with each agent. [ABSTRACT FROM AUTHOR]

The inherent ambiguity in reconstructed images from coherent diffraction imaging (CDI) poses an intrinsic challenge, as images derived from the same dataset under varying initial conditions often display inconsistencies. This study introduces a method that employs the Noise2Noise approach combined with neural networks to effectively mitigate these ambiguities. We applied this methodology to hundreds of ambiguous reconstructed images retrieved from a single diffraction pattern using a conventional retrieval algorithm. Our results demonstrate that ambiguous features in these reconstructions are effectively treated as inter‐reconstruction noise and are significantly reduced. The post‐Noise2Noise treated images closely approximate the average and singular value decomposition analysis of various reconstructions, providing consistent and reliable reconstructions. [ABSTRACT FROM AUTHOR]

This paper is devoted to reduce the conservativeness of distributionally robust optimization with moments information. Since the optimal solution of distributionally robust optimization is required to be feasible for all uncertain distributions in a given ambiguity distribution set and so the conservativeness of the optimal solution is inevitable. To address this issue, we introduce the globalized distributionally robust counterpart (GDRC) which allows constraint violations controlled by functional distance of the true distribution to the inner distribution set. We obtain the deterministic equivalent forms for several GDRCs under the moment-based framework. To be specific, we show the deterministic equivalent systems of inequalities for GDRCs under second order moment information with a separable convex distance function and a special jointly convex function, respectively. We also obtain the deterministic equivalent inequality for GDRC under first order moment and support information. The computationally tractable examples are presented for these GDRCs. Numerical tests of a portfolio optimization problem are given to show the effectiveness of our method and the results demonstrate that the globalized distributionally robust solution is non-conservative and flexible compared to the distributionally robust solution. [ABSTRACT FROM AUTHOR]

Researchers and manufacturers use the Precise Point Positioning (PPP) technique. After the phase biases of the satellites are resolved from GNSS networks, they are broadcast to users as Fractional Cycle Bias (FCB). In this study, FCB products provided by WUHAN, CODE, CNES and JAXA services were downloaded and PPP Ambiguity Resolution solutions were realised by Net_Diff software. For ten days in 2022, 24-hour observations were collected from 40 International GNSS Service stations. As a result, it has been observed that WUHAN and CODE services provided the ±1 cm or ±5 cm accuracy level by converging in short-term observations. [ABSTRACT FROM AUTHOR]

One of the obstacles in the study of post-classical Sufi literatures has been the sceptical attitude toward Sufi commentary on Arabic and Persian lyrical poetry (specifically 'mystical' or 'Sufi allegorical' readings of the lyric). This attitude has prevented a wider appreciation of Sufi interpretations of such poetry. While there are signs of a shift in attitudes as scholars grapple with different Sufi commentators and their discussions of notable verses, many still hold to their scepticism. Although studies of individual commentaries will be necessary to reform these attitudes, a general response to the sceptical views may help to orient those studies, particularly one that draws its evidence and arguments from representative Sufi commentators and theorists of the lyric. This paper attempts such a response. Following a brief outline of critiques of Sufi commentary, and the reasons for continued scepticism toward commentators, I suggest how shifting understandings around the ambiguity present in the lyric should help to make allegorical interpretations seem more plausible as a collection of meanings in the archive that was persuasive to many readers, the figurative language of the lyric being able to support both literary-historical and allegorical interpretations of words, phrases, or images in particular verses. Sufi commentators used this ambiguity as a means by which to explore the meanings of the allegory according to the principle 'The figurative is the bridge to the Truth–Reality'. Sufi theorists, moreover, discussed how the figurative language of the lyric and its allegoresis by way of commentary could serve distinct functions for different kinds of readers in Sufi knowledge–practice. If the figurative form of the lyric was more suitable for non-Sufi readers or novices in Sufism to encounter its 'specific meanings', commentary, expressed in the technical language of Sufism, could assist more advanced Sufi readers to verify its 'general meanings'. Far from diminishing the lyric, Sufi commentary only enhanced its value, showing it to possess both literary beauty as well as profound depth of meaning. I invoke Paul Griffiths's 'religious reading' to suggest that an approach to the lyric that privileges the views of Sufi commentators is not only feasible, it can even be valuable for specialists of the lyric in the contemporary academy. [ABSTRACT FROM AUTHOR]

How atmospheric pollution is perceived by urban dwellers has long been a topic of interest within geography and the social sciences, whether to draw attention to environmental injustices, to better understand the materialities and affects associated with polluted air, or to grasp how people 'tune in' to polluted matter. In this paper, we draw on three interrelated geographical and social science literatures on polluted air to inform our exploration of how residents of an industrial town in the UK encounter and perceive localised ambient air pollution. Using creative methods, we explore residents' narrative accounts of everyday life in the town, revealing how their engagements with the matter of pollution over time are drawn from multiple registers, giving rise to a plurality of perceptions filled with tensions between near and far, and between past, present and future, producing an ambiguous atmosphere all of its own. The paper contributes to geographic explorations of urban atmospheres an understanding of how they are differently experienced and known, and how residential perceptions might persist or change over different timescales. [ABSTRACT FROM AUTHOR]

Prostate Imaging Reporting and Data System (PI-RADS) was designed to standardize the interpretation of multiparametric magnetic resonance imaging (MRI) of the prostate, aiding in assessing the probability of clinically significant prostate cancer. By providing a structured scoring system, it enables better risk stratification, guiding decisions regarding the need for biopsy and subsequent treatment options. In this article, we explore both the strengths and weaknesses of PI-RADS, offering insights into its updated diagnostic performance and clinical applications, while also addressing potential pitfalls using diverse, representative MRI cases. [ABSTRACT FROM AUTHOR]

With the development of deep learning, Remote Sensing Image (RSI) semantic segmentation has produced significant advances. However, due to the sparse distribution of the objects and the high similarity between classes, the task of semantic segmentation in RSI is still extremely challenging. In this paper, we propose a novel semantic segmentation framework for RSI called HST-UNet that can overcome the shortcomings of the existing models and extract and recover the global and local features of RSI, which is a hybrid semantic segmentation model with Shunted Transformer as encoder and Multi-Scale Convolutional Attention Network (MSCAN) as decoder. Then, to better fuse the information from the Encoder and the Decoder and alleviate the ambiguity, we design a Learnable Weighted Fusion (LWF) module to effectively connect to the decoder features. Extensive experiments demonstrate that the proposed HST-UNet outperforms the state-of-the-art methods, achieving F1 score/MIoU accuracy of 71.44%/83.00% on the ISPRS Vaihingen dataset and 77.36%/87.09% on ISPRS Potsdam dataset. The code will be available at https://github.com/HC-Zhou/HST-UNet. [ABSTRACT FROM AUTHOR]

The genus Pseudamnicola Paulucci, 1878, is commonly found throughout the Mediterranean region. The genus displays considerable levels of endemism, accompanied by notable systematic and taxonomic ambiguity. However, the application of molecular data has proven highly effective in clarifying taxonomy and unveiling the diversity of cryptic species within the genus. Therefore, we employed all cytochrome c oxidase subunit I sequence data available and generated new ones from Greece to infer the phylogeny of the genus throughout its Mediterranean range and estimate the divergence times as well as the ancestral area of diversification. Our phylogenetic and time‐estimate analyses demonstrate that with 36 to 38 extant Pseudamnicola species and genetic divergences across species ranging from 0.5% to 11.9% on average, the genus underwent relatively recent diversification during late Miocene (6.53 Ma), and the primary speciation events occurred during Plio‐Pleistocene. The Italian Peninsula and Islands and the Ionian Drainages as defined by the Freshwater Ecoregions of the World are the ancestral regions of the genus following two different dispersal routes. Our study contributes to deepening our understanding of Pseudamnicola phylogeny by using data from throughout its range for the first time. This phylogeny provides evidence and confirms previous studies that relatively recent habitat isolation, followed by founder and dispersal events, has been one of the primary reasons for the evolution of the genus Pseudamnicola in the Mediterranean basin. [ABSTRACT FROM AUTHOR]

This article contributes to an understanding of humour in political communication, particularly in official institutional communication. Specifically, it analyses the 'special heroes' campaign, which the German government published on its social media channels in November 2020. The campaign spoofed the COVID-19-specific heroification of certain groups of society by creating a humorous 'special hero' discourse of the ongoing pandemic. This humour is highly political, as it tries to influence the personal life and behaviour of citizens. Furthermore, it makes citizens responsible, and turns those affected by the pandemic into heroes. This article will adopt a method inspired by the Discourse Historical Approach which, along with context, focuses on the three elements of content, strategies, and linguistic means of realisation. It shows how humour in the form of parody can be favourable when done professionally by using the ambiguity of sensitive topics like war. It also shows how parodic forms can motivate users to create further parodies of the original content, thereby cementing the message of the government. [ABSTRACT FROM AUTHOR]

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To solve this issue of phase estimation ambiguity induced by Gaussian-filtered minimum shift keying (GMSK) phase continuity, a GMSK coherent receiving algorithm based on optimal sampling point is proposed. For realizing the decoupling of symbols, a preceding method in constructed to encode original message to modulate and then the receiver samples at optimal time with minimal intersymbol interference to transform GMSK into offset quadrature phase shift keying (OQPSK), effectively avoiding this issue of Doppler frequency and phase inaccurate estimation induced by the introduction of initial phase ambiguity from previous unknown data. A coherent demodulator in built based on optimal sampling time to accomplish reliable receiving with low complexity. Simulation results indicate that the proposed method has a higher estimation range of Doppler frequency, while comparable estimation precision. Meanwhile, compared to optimal receiver, the proposed demodulation algorithm has very small complexity and comparable demodulation performance. [ABSTRACT FROM AUTHOR]

We propose a model‐guided option‐implied ambiguity measure to capture uncertainty regarding the return distribution of a risky asset underlying a set of options, and investigate its predictive power on the asset return. A representative investor's ambiguous beliefs or prior distributions on the underlying asset returns are extracted from the market prices of options, the expected volatility of which is then defined as the option‐implied ambiguity and is calculated in line with Brenner and Izhakian. Simulated paths of the calibrated models are utilized to compute all pertinent probability characteristics from a forward‐looking perspective. The empirical results with SSE 50 ETF options indicate that the proposed option‐implied ambiguity has strong predictive power for future returns of SSE 50 ETF. Out‐of‐sample tests also verify the significant predictive ability of the option‐implied ambiguity to the equity returns. [ABSTRACT FROM AUTHOR]

Negation is a universal linguistic phenomenon that affects the performance of Natural Language Processing (NLP) applications, especially opinion mining data. Many words exists in sentences that have multiple interpretations or sentiments depending on how they are placed with respect to the negation word in the sentence. A cutting-edge framework is designed to tackle the nuanced challenge of detecting contextual ambiguity through negation in sentiment analysis. The approach uniquely combines advanced natural language processing techniques with deep linguistic insights, enabling the accurate interpretation of sentiment in complex sentences where negation plays a key role. The framework identifies negation cues and their scope, then assesses their impact on sentiment, considering contextual dependencies and word semantics. The model's innovation lies in context-sensitive algorithms that adeptly handle different sentence structures and idiomatic expressions, a notable advancement over traditional sentiment analysis tools. Particularly effective in interpreting sarcastic or ironic statements, the framework significantly outperforms existing models in accuracy, especially in negation-heavy contexts. This advancement enhances sentiment analysis applications like social media monitoring and customer feedback analysis, offering a more nuanced understanding of public opinion. [ABSTRACT FROM AUTHOR]

Purpose: Business strategy issues increasingly concern value realized from supply resources. However, how supply resources are valorized by managerial factions in a strategic issue setting is not sufficiently explored. In organizations operating in complex business contexts, several strategic agendas and supply value perceptions typically coexist. This study aims to explore the process of developing corporate attention towards supply-related strategic issues and how it links to sourcing strategy. Design/methodology/approach: An explorative longitudinal case study within the food industry is conducted. Data are collected in a four year period. Working physically from the case company made it possible to be close to the company's actors. The first author participated in 26 formal team meetings ranging from 1.5 h to 3 days long, conducted 28 interviews across managerial levels and functions and participated in informal verbal and written communications. Findings: This study explores strategizing efforts of organizations and scrutinize consequences of strategic ambiguity for sourcing strategy and supply resources. Furthermore, this study outlines implications for management and theory development. Research limitations/implications: Since this paper is based on an in-depth single case study, its findings are not empirically generalizable. Practical implications: This paper suggests that managers should pay stronger attention to constituents' valuation of supply resources, and how they fit with the different strategic agendas within the firm. By doing so, a more comprehensive supply resource mobilization is possible. Originality/value: Business strategy research increasingly focuses on the value of supply resources for a buying firm's business strategy (Kotabe and Murray 2018; Lee and Rammohan 2017; Schiele, Calvi, and Gibbert 2012). In a context where the value obtained from sourcing is gaining increased importance, more organizations link supply policies with corporate strategic goals (Andersen, Ellegaard, and Kragh 2016; Hesping and Schiele 2015; Pardo et al., 2011). However, existing supply chain research does not incorporate an organization's strategizing efforts, when considering supply resource valuation, and how this can be a source of ambiguity to sourcing strategy. The is the paper's contribution. [ABSTRACT FROM AUTHOR]

This article explores the challenges of understanding statistical language, particularly for students. The author shares their own struggles with mastering statistical language and highlights the issue of lexical ambiguity, where statistical terms have different meanings than their everyday counterparts. The lack of standardization in statistical language and the confusion caused by different terms for the same concepts are also discussed. The article emphasizes the importance of understanding statistical language for full participation in the discipline and suggests the need for careful language choice and awareness of lexical ambiguity. Different approaches to terminology and definitions are explored, with an emphasis on finding a balance between mathematical and linguistic requirements. The article acknowledges the difficulty of achieving a perfect solution to these challenges. [Extracted from the article]

Beta coefficients for linear regression models represent the ideal form of an interpretable feature effect. However, for non-linear models such as generalized linear models, the estimated coefficients cannot be interpreted as a direct feature effect on the predicted outcome. Hence, marginal effects are typically used as approximations for feature effects, either as derivatives of the prediction function or forward differences in prediction due to changes in feature values. While marginal effects are commonly used in many scientific fields, they have not yet been adopted as a general model-agnostic interpretation method for machine learning models. This may stem from the ambiguity surrounding marginal effects and their inability to deal with the non-linearities found in black box models. We introduce a unified definition of forward marginal effects (FMEs) that includes univariate and multivariate, as well as continuous, categorical, and mixed-type features. To account for the non-linearity of prediction functions, we introduce a non-linearity measure for FMEs. Furthermore, we argue against summarizing feature effects of a non-linear prediction function in a single metric such as the average marginal effect. Instead, we propose to average homogeneous FMEs within population subgroups, which serve as conditional feature effect estimates. [ABSTRACT FROM AUTHOR]

Data Envelopment Analysis is applied to a sample of IT projects. The application is based on a discussion concerning the choice of inputs and outputs in the case when the units being evaluated are projects. This discussion takes into account various understandings of project success and thus project desired outputs, as well as the ambiguity and a strong situation dependence concerning the choice of project inputs, understood as variables that should be minimized. The sample consists of over 80 IT projects implemented in Poland. The applied DEA model has permitted to identify the projects that clearly stand out from the rest of the sample as less efficient. Their analysis made it possible to draw conclusions on the choice of inputs and outputs. A set of indications on the context-specific choice of inputs and outputs were formulated. [ABSTRACT FROM AUTHOR]

A subjective expected utility maximizer is usually considered to be neutral to ambiguity (Knightian uncertainty). Arguably, a decision-maker who behaves as if he or she forms probabilistic beliefs over uncertain events (but does not necessarily maximize expected utility) is also ambiguity neutral. This note proposes a simple definition of (absolute) ambiguity neutrality in choice under Knightian uncertainty: if a decision-maker bets more money on event A rather than on event B then he or she should also consistently bet less money on event B (rather than on event A). This definition is consistent with the classic Ellsberg two- and three-color paradoxes. [ABSTRACT FROM AUTHOR]

A family of familiar linguistic tests purport to help identify when a term is ambiguous. These tests are philosophically important: a familiar philosophical strategy is to claim that some phenomenon is disunified and its accompanying term is ambiguous. The tests have been used to evaluate disunification proposals about causation, pain, and knowledge, among others. These ambiguity tests, however, have come under fire. It has been alleged that the tests fail for polysemy: a common type of ambiguity, and one that is at issue in philosophically interesting cases. Furthermore, the objection that the tests fail for polysemy is often taken to be an undeniable bit of linguistic data. We argue that this is mistaken. The objection implicitly relies on controversial assumptions about how to account for copredicational sentences, in which a single argument is ascribed prima facie incompatible properties. Furthermore, on several viable theories of copredication, the objection fails. However, our discussion also reveals that even if ambiguity tests are preserved, they may be significantly harder to execute than previously thought. [ABSTRACT FROM AUTHOR]

The article is a review of the book "Fathom: An Uncovering of Trauma" by Lisa Dart. The book is described as a creative memoir about trauma, focusing on the author's experiences and her exploration of the connection between childhood experiences and adult emotions. The review discusses the use of imagery and paintings in the book, as well as the narrator's fascination with color. It also explores the narrator's relationship with her father and her struggle with mental illness. Overall, the book is praised for its exploration of madness, remembrance, and creativity. [Extracted from the article]

Small and medium-sized enterprises (SMEs) are the backbone of many economies. In today's world of VUCA (Volatility, Uncertainty, Complexity, Ambiguity), SMEs face diverse challenges to survive and stay competitive. SMEs must prepare themselves for these challenges by practicing foresight. However, foresight, and especially corporate foresight, has been conceptualized and researched in the context of large corporations. Applying foresight in SMEs is therefore complicated by the question of how to implement foresight in the context of SMEs given their specific requirements and limitations. This article provides an overview on the literature on the application of foresight in SMEs is, along with a summary of the extent to which SMEs conduct foresight from an organizational and individual perspective. Besides offering a compendium on the state of foresight in SMEs, a research agenda is formulated, incorporating the idea of a toolbox tailored to SMEs based on existing approaches and prior works. [ABSTRACT FROM AUTHOR]

This paper explores the interplay between romantic family imaginaries and asexual identity-making through the agentic negotiation of pragmatic trade-offs. Romantic family imaginaries refer to ideational and aspirational aspects of idealized romantic relationships that mark them as chosen family and engender associated feelings of security and normalcy. I analysed idiographic case studies (chosen from a larger sample of 44 interviewees) of two interviewees with asexual tendencies, romantic family aspirations, and ambivalence towards asexual identification. Romantic family imaginaries accentuated ambiguities in how my interviewees experienced and labelled their asexual feelings. Extending ideas about pragmatism explored within family studies and queer Singapore studies, this research conceptually proposes two ways through which pragmatic negotiation may take place: the deployment of provisional and prospective identities. Provisional identities affirm ambiguity by tethering themselves to ongoing relationships that live out family imaginaries. Prospective identities affirm ambiguity by qualifying themselves in relation to future unknowns. Examining these trade-offs reveals how romantic and sexual normativity, usually thought to be allied, may sometimes be situationally opposed. [ABSTRACT FROM AUTHOR]

Antifragility is a concept that has been described as beyond resilience – not simply resisting shock but becoming better as a result. Using a nationally representative survey of 783 low-income U.S. veterans in 2022–2023, a measure of antifragility was developed and tested. The results were replicated on a supplementary sample of 245 veterans. A 12-item measure of antifragility was developed, consisting of three factors/subscales labeled Benefit from Difficulty, Benefit from Ambiguity and Benefit from Stress. The scale demonstrated good psychometric properties. In main and replication samples, 2–4% reported overall antifragility ‘often’ or ‘nearly all the time’. Respondents reported antifragility in various areas of life, the most common being 60–61% in family life/children and 60–62% in social relationships/friends. These findings suggest antifragility is common in many areas of life, but high levels are rare. This study provides a measure of antifragility, and further testing is needed to assess its predictive value. [ABSTRACT FROM AUTHOR]

Mesophyll conductance (gm ${g}_{{\rm{m}}}$) describes the efficiency with which CO2 ${\mathrm{CO}}_{2}$ moves from substomatal cavities to chloroplasts. Despite the stipulated importance of leaf architecture in affecting gm ${g}_{{\rm{m}}}$, there remains a considerable ambiguity about how and whether leaf anatomy influences gm ${g}_{{\rm{m}}}$. Here, we employed nonlinear machine‐learning models to assess the relationship between 10 leaf architecture traits and gm ${g}_{{\rm{m}}}$. These models used leaf architecture traits as predictors and achieved excellent predictability of gm ${g}_{{\rm{m}}}$. Dissection of the importance of leaf architecture traits in the models indicated that cell wall thickness and chloroplast area exposed to internal airspace have a large impact on interspecific variation in gm ${g}_{{\rm{m}}}$. Additionally, other leaf architecture traits, such as leaf thickness, leaf density and chloroplast thickness, emerged as important predictors of gm ${g}_{{\rm{m}}}$. We also found significant differences in the predictability between models trained on different plant functional types. Therefore, by moving beyond simple linear and exponential models, our analyses demonstrated that a larger suite of leaf architecture traits drive differences in gm ${g}_{{\rm{m}}}$ than has been previously acknowledged. These findings pave the way for modulating gm ${g}_{{\rm{m}}}$ by strategies that modify its leaf architecture determinants. [ABSTRACT FROM AUTHOR]

This paper explores the deliberate use of temporal ambiguities and discrepancies in Defoe’s The Fortunate Mistress to convey the disturbed retrospections of a guilt/shame-ridden narrator and the relationship between moral injury and temporal narrative techniques, highlighting the gendered nature of the fictional narrator’s moral injury. Drawing on Pederson’s model of moral injury in literature, which deals with perpetrator trauma, it argues that the narrator’s moral injury and its temporal reflexes in the narrative serve to reinforce the thematic and narratorial (re)iterations of female trauma and subsequent moral injury. Ultimately, this analysis provides compelling evidence of Defoe’s astute understanding of the psychology of shame, guilt, and narration, as well as his preference for psychological realism over traditional sequential narration, as he crafts stories that explore the human and psychological consequences of traumatic experiences. [ABSTRACT FROM AUTHOR]

Ambiguity resolution (AR) can markedly enhance the precision of precise point positioning (PPP) and accelerate the convergence process. The decoupled clock model represents a pivotal approach for ambiguity resolution, yet current research on this topic is largely confined to GPS. Consequently, in this study, we extend the investigation of the decoupled clock model to multi-GNSS. Firstly, based on the conventional model, we derive the multi-GNSS decoupled clock estimation model and the precise point positioning with ambiguity resolution (PPP-AR) model. Secondly, we provide a detailed explanation of the estimation process for the multi-GNSS decoupled clock estimation. To validate the efficacy of the proposed model, we conduct multi-GNSS decoupled clock estimation and PPP-AR experiments using six days of observation data. The results demonstrate that the decoupled clocks of GPS, Galileo, and BDS-3 can all achieve high accuracy, thus fully meeting the requirement of ambiguity resolution. In terms of positioning performance, the joint three systems have higher positioning accuracy, reaching 3.10 cm and 6.13 cm in horizontal and vertical directions, respectively. Furthermore, the convergence time (CT) and time to first fix (TTFF) are shortened, to 23.13 min and 13.65 min, respectively. The experimental findings indicate that the proposed multi-GNSS decoupled clock model exhibits high precision and rapid positioning service capabilities. [ABSTRACT FROM AUTHOR]

Long-distance Real-Time Kinematic (RTK) positioning is crucial for applications in remote areas, such as maritime environments. Achieving 2–3 cm accuracy with RTK requires successful ambiguity resolution, which involves two main steps: identifying the best integer ambiguity candidate and confirming its validity. While previous research has largely concentrated on the first step, including the development of Cascading Ambiguity Resolution methods, and reducing tropospheric delay, studies on the validation of ambiguity for long-distance RTK are limited. This study conducts a thorough examination of ambiguity validation for long-distance RTK, focusing on two prevalent methods: the theoretical success rate and the R-ratio test. The results reveal several key insights. Firstly, the six commonly used bounds for the theoretical success rate are not an accurate reflection of the actual success rate, making them unsuitable for long-distance RTK applications. Secondly, the R-ratio test proves to be dependable when the threshold is set above 1.7, assuming there is a minimum observation period of one minute and at least ten satellites are visible. However, the probability of successfully resolving ambiguities with the R-ratio test does not surpass 50%. Additionally, if ambiguity resolution is not achieved within 20 min, simply prolonging the observation time is generally unproductive. To improve the performance of ambiguity resolution in practical situations that require extended observation times, this research proposes a novel ambiguity validation method. This new approach is based on the duration for which an integer ambiguity resolution candidate maintains the best status. This method aims to provide a reliable means of validating ambiguities in cases where the R-ratio test fails. [ABSTRACT FROM AUTHOR]

Complex neutrosophic soft groups represent a significant advancement in handling uncertainty by integrating the concepts of fuzzy logic, soft sets, and neutrosophic logic. These groups generalize complex fuzzy soft groups and introduce an additional dimension through neutrosophic membership functions, namely truth, indeterminacy, and falsity. This creates a richer framework for dealing with uncertainty and ambiguity, making it well-suited for managing complex data structures in real-world applications. We explore some important definitions and theoretical frameworks surrounding complex neutrosophic soft groups, highlighting the unique aspect of neutrosophic membership functions. Additionally, we present an overview of neutrosophic soft groups, exploring some of their key operations and fundamental properties. We then examine the basics of homogeneous complex neutrosophic soft sets and their roles in establishing complex neutrosophic soft groups. [ABSTRACT FROM AUTHOR]

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Recent theoretical developments in economics distinguish between risk and ambiguity (Knightian uncertainty). Using state-of-the-art methods with intraday stock market data from February 1993 to February 2021, we derive financial ambiguity and empirically examine the effect of shocks to it on the price and volatility of crude oil. We provide evidence that ambiguity carries important information about future oil returns and volatility perceived by investors. We validate these results using Granger causality and in-sample and out-of-sample forecasting tests. Our findings reveal that financial ambiguity is a possible factor that explains future drops in oil prices and their increased variability. Our findings will benefit scholars and investors interested in how financial ambiguity shapes short-term oil prices. [ABSTRACT FROM AUTHOR]

Various stress-releasing phenomena, such as episodic tremor and slip (ETS) and low-frequency earthquakes, occur at the downdip seismogenic zone in southwest Japan. However, it is unclear how much net stress and slip deficit accumulate at these depths during the interseismic phase. Here, we perform both elastic and viscoelastic earthquake-cycle forward models and reassess the locking state in Nankai from a synthesized perspective with the aid of geodetic modeling results. Our results suggest that the overestimation of the locking depth due to ignoring Earth's viscoelasticity is much smaller (less than 5 km) in this early interseismic subduction zone compared to that (~ 10 km) of late-interseismic margins. Considering viscoelastic modeling results and other physical arguments, the preferred steady-state viscosities for the continental and oceanic mantle are 5 × 1019 Pa s and 1020 Pa s, respectively. We find a clear trade-off between the full locking depth and the width of the transition zone when explaining both horizontal and vertical geodetic data, demanding other data to further resolve this inherent ambiguity. Unlike in Cascadia, partial megathrust locking in Nankai likely penetrates into the ETS zone, leaving no intervening gap between the shallow megathrust, where hosts large earthquakes, and the ETS zone. Assuming locking extends into the downdip of the ETS zone (i.e., 40 km), we propose a preferred viscoelastic locking model with a full locking depth of 18 km and a broad transition zone spanning a 22-km depth range. In this model, the downdip half portion of the transition zone corresponds to the ETS zone, which can accumulate certain slip deficit in a largely creeping and partially locked state. However, most of the accumulated slip deficit in the ETS zone may be accommodated aseismically simultaneously by stress-releasing phenomena, leaving limited to no budget to release during future megathrust earthquakes. We suggest that precise documentation of total slip during slow slip events, along with refinement of viscoelastic locking models, will provide new insights into the net slip budget available in the ETS zone. This will help assess the potential of future coseismic and/or postseismic slip penetrating into the ETS zone in Nankai, Cascadia and other subduction zones. [ABSTRACT FROM AUTHOR]

Humans possess a remarkable ability to efficiently process faces, a skill largely influenced by their experiences with individual faces. However, recent research has challenged the role of experience in holistic face processing. Our study examined the role of face-race experience in holistic face processing among Asian and White adults using Asian, White, and racially ambiguous faces. The findings showed that both Asians and Whites exhibited reliable holistic processing for their own-race faces but failed to exhibit this ability with racially ambiguous faces. Importantly, the failure was not solely due to the specific morphing procedure or response bias. These findings imply that face-race experience plays a crucial role in holistic processing. Notably, Asians maintained holistic processing for both own-race and other-race faces, whereas Whites only showed this for own-race faces, indicating differential impacts of face-race experience on holistic processing and highlight the need for further research across diverse cultural contexts.HighlightsAsian adults showed equivalent holistic processing with Asian and Caucasian facesCaucasian adults showed holistic processing with Caucasian faces but not with Asian facesBoth Asian and Caucasian adults did not show holistic processing with racially ambiguous facesAsian adults showed equivalent holistic processing with Asian and Caucasian facesCaucasian adults showed holistic processing with Caucasian faces but not with Asian facesBoth Asian and Caucasian adults did not show holistic processing with racially ambiguous faces [ABSTRACT FROM AUTHOR]

We show that the finite sequentiality problem is decidable for finitely ambiguous max-plus tree automata. A max-plus tree automaton is a weighted tree automaton over the max-plus semiring. A max-plus tree automaton is called finitely ambiguous if the number of accepting runs on every tree is bounded by a global constant. The finite sequentiality problem asks whether for a given max-plus tree automaton, there exist finitely many deterministic max-plus tree automata whose pointwise maximum is equivalent to the given automaton. [ABSTRACT FROM AUTHOR]

Before exploiting a geothermal resource in a volcanic setting such as the Asal rift, it is necessary to acquire a better knowledge of the subsoil, with the objective of locating the geothermal reservoir and evaluating the resource characteristic (permeability, temperature, etc.). For this type of resource, geophysical exploration methods are essential (such as gravimetry, magnetotellurics, etc.). However, a particular data type does not necessarily have the resolution and sensitivity. Furthermore, individual inversions of these geophysical data face the ambiguity of the non‐uniqueness of the inverse solution. In this paper, we present a new linear approach of gravity data using the constraint of a MT resistivity model. We coupled the resistivity and density using inversion cross‐gradients and the linear correlations. The approach was tested and validated on synthetic data and applied to gravity and MT data in the Asal Rift. Multiple inversions with different levels of coupling provided a series of density models. We applied the principal component analysis (PCA) technique to assess these models. We were able to define two dominant processes acting differently on the density and resistivity distribution at depth, namely the geothermal activity of the rift and the structural control of active tectonics. Plain Language Summary: The inversion of geophysical data faces the problem of ambiguity or nonuniqueness. Constrained inversion can be an effective solution to reduce these ambiguities. Coupling several geophysical methods provides a priori information to help sample the space of acceptable models toward a reliable and realistic solution. In order to assess the resulting models, we use multivariate statistics. We present two types of coupling, cross‐gradient and linear correlation between density and electrical resistivity. The approach was tested and validated on synthetic data and on data acquired in the Asal rift, Republic of Djibouti. The results suggest that both the geothermal activity of the rift and the structural control of active tectonics control the distribution of density and electrical resistivity. Key Points: We developed a new constrained inversion using the cross‐gradient and linear correlation couplings between density and resistivityThe models resulting from these two inversions are synthesized using the principal component analysis methodResistivity and density models highlight that the Asal rift is dominated by more than one process (geothermal and tectonic) [ABSTRACT FROM AUTHOR]

This paper refutes the common objection against pantheistic models of divinity that they are valueless or bereft of ethics due to the ambiguous model of God they espouse, arguing instead that pantheism can be construed as an inherently ethical model of divinity. It addresses common assumptions about omnibenevolent deities and the values they do or do not inspire. It then discusses the values that are arguably both immanent and inherent in nature itself. Finally, this paper makes the case that the ambiguity that pantheistic models of God acknowledge in nature is actually a necessary precondition for goodness itself. [ABSTRACT FROM AUTHOR]