bluuebunny/crossref_metadata_2025_split huggingface dataset:
Primary productivity in subsidized green-brown food webs
Authors: Zelnik Yuval R. , Manzoni Stefano , Bommarco Riccardo 
Published: December 2021

1AbstractEcosystems worldwide receive large amounts of nutrients from both natural processes and human activities. While direct subsidy effects on primary productivity are relatively well known (the green food web), the indirect effects of subsidies on producers as mediated by the brown food web and predators have been neglected. With a dynamical green-brown food web model, parameterized using empirical estimates from the literature, we illustrate the effect of nutrient subsidies on net primary productivity (i.e., after removing loss to herbivory) in two generic ecosystems, terrestrial and aquatic. We find that nutrient subsidies increase net primary productivity because more nutrients are available, but this effect saturates with higher subsidies. Changing the quality of subsidies from inorganic to organic tends to increase net primary productivity in terrestrial ecosystems, but less often so in aquatic ecosystems. This occurs when organic nutrient inputs promote detritivores in the brown food web, and hence predators that in turn control herbivores, thus promoting primary productivity. This previously largely overlooked effect is further enhanced by ecosystem properties such as fast decomposition and low rates of nutrient additions, and demonstrates the importance of nutrient subsidy quality on ecosystem functioning.
Neural mechanisms of credit assignment for inferred relationships in a structured world
Authors: Witkowski Phillip P. , Park Seongmin A. , Boorman Erie D. 
Published: December 2021

AbstractAnimals have been proposed to abstract compact representations of a task’s structure that could, in principle, support accelerated learning and flexible behavior. Whether and how such abstracted representations may be used to assign credit for inferred, but unobserved, relationships in structured environments are unknown. Here, we develop a novel hierarchical reversal-learning task and Bayesian learning model to assess the computational and neural mechanisms underlying how humans infer specific choice-outcome associations via structured knowledge. We find that the medial prefrontal cortex (mPFC) efficiently represents hierarchically related choice-outcome associations governed by the same latent cause, using a generalized code to assign credit for both experienced and inferred outcomes. Furthermore, mPFC and lateral orbital frontal cortex track the inferred current “position” within a latent association space that generalizes over stimuli. Collectively, these findings demonstrate the importance both of tracking the current position in an abstracted task space and efficient, generalizable representations in prefrontal cortex for supporting flexible learning and inference in structured environments.
Fast Medical Image Auto-segmentation for Bleeding Gastric Tissue Detection based on Deep DuS-KFCM Clustering
Authors: Liu Xian-Xian , Li Gloria , Luo Wei , Gao Juntao , Fong Simon 
Published: December 2021

AbstractBackgroundDetection and classification of gastric bleeding tissues are one of the challenging tasks in endoscopy image analysis. Lesion detection plays an important role in gastric cancer (GC) diagnosis and follow-up. Manual segmentation of endoscopy images is a very time-consuming task and subject to intra- and interrater variability. Accurate GB segmentation in abdominal sequences is an essential and crucial task for surgical planning and navigation in gastric lesion ablation. However, GB segmentation in endoscope is a substantially challenging work because the intensity values of gastric blood are similar to those of adjacent structures.ObjectiveIn this paper the idea is to combine two parts: Neural Network and Fuzzy Logic--Hybrid Neuro-Fuzzy system. The objective of this manuscript is to provide an efficient way to segment the gastric bleeding lesion area. This work focuses on design and development of an automated diagnostic system using gastric bleeding cancer endoscopy images.MethodsIn this paper, a coarse-to-fine method was applied to segment gastric bleeding lesion from endoscopy images, which consists of two stages including rough segmentation and refined segmentation. The rough segmentation is based on a kernel fuzzy C-means algorithm with spatial information (SKFCM) algorithm combined with spatial gray level co-occurrence matrix (GLCM) and the refined segmentation is implemented with deeplabv3+ (backbone with resnet50) algorithm to improve the overall accuracy.ResultsExperimental results for gastric bleeding segmentation show that the method provides an accuracy of 87.9476% with specificity of 96.3343% and performs better than other related methods.onclusionsThe performance of the method was evaluated using two benchmark datasets: The GB Segmentation and the healthy datasets. Then use the gastric red spots (GRS) dataset to do the final test to verify weak bleeding symptoms. Our method achieves high accuracy in gastric bleeding lesion segmentation. The work describes an innovative way of using GLCM based textural features to extract underlying information in gastric bleeding cancer imagery. Modified deep DuS-KFCM endoscopy image segmentation method based on GLCM feature, The experimental results shown to be effective in image segmentation and has good performance of resisting noise, segmentation effect more ideal.
MAVS mediates a protective immune response in the brain to Rift Valley fever virus
Authors: Hum Nicholas R. , Bourguet Feliza A. , Sebastian Aimy , Lam Doris , Phillips Ashlee M. , Sanchez Kristina R. , Rasley Amy , Loots Gabriela G. , Weilhammer Dina R. 
Published: December 2021

AbstractRift Valley fever virus (RVFV) is a highly pathogenic mosquito-borne virus capable of causing hepatitis, encephalitis, blindness, hemorrhagic syndrome, and death in humans and livestock. Upon aerosol infection with RVFV, the brain is a major site of viral replication and tissue damage, yet pathogenesis in this organ has been understudied. Here, we investigated the immune response in the brain of RVFV infected mice. In response to infection, microglia initiate robust transcriptional upregulation of antiviral immune genes, as well as increased levels of activation markers and cytokine secretion that is dependent on mitochondrial antiviral-signaling protein (MAVS) and independent of toll-like receptors 3 and 7. In vivo, Mavs-/- mice displayed enhanced susceptibility to RVFV as determined by increased brain viral burden and higher mortality. Single-cell RNA sequence analysis identified microglia-specific defects in type I interferon and interferon responsive gene expression in Mavs-/- mice, as well as dysregulated lymphocyte infiltration. The results of this study provide a crucial step towards understanding the precise molecular mechanisms by which RVFV infection is controlled in the brain and will help inform the development of vaccines and antiviral therapies that are effective in preventing encephalitis.Author SummaryRift Valley fever virus causes severe disease in humans and livestock and in some cases can be fatal. There is concern about the use of Rift Valley fever virus as a bioweapon since it can be transmitted through the air, and there are no vaccines or antiviral treatments. Airborne transmission of the virus causes severe inflammation of the brain, yet little is known about the immune response against the virus in this organ. Here, we investigated the immune response in the brain to Rift Valley fever virus following intranasal infection. We determined that microglia, the resident immune cells of the brain, initiate a robust response to Rift Valley fever virus infection and identified a key immune pathway that is critical for the ability of microglia to respond to infection. When this immune pathway is rendered non-functional, mice have a dysregulated response to infection in the brain. This study provides insight into how the immune response can control Rift Valley fever virus infection of the brain.
Single-nucleus RNA Sequencing and Spatial Transcriptomics Reveal the Immunological Microenvironment of Cervical Squamous Cell Carcinoma
Authors: Ou Zhihua , Lin Shitong , Qiu Jiaying , Ding Wencheng , Ren Peidi , Chen Dongsheng , Wang Jiaxuan , Tong Yihan , Wu Di , Chen Ao , Deng Yuan , Cheng Mengnan , Peng Ting , Lu Haorong , Yang Huanming , Wang Jian , Jin Xin , Ma Ding , Xu Xun , Wang Yanzhou , Li Junhua , Wu Peng 
Published: December 2021

AbstractEffective treatment of advanced invasive cervical cancer remains challenging nowadays. Herein, single-nucleus RNA sequencing (snRNA-seq) and SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq) technology are used to investigate the immunological microenvironment of cervical squamous cell carcinoma (CSCC), a major type of cervical cancers. The expression levels of most immune checkpoint genes in tumor and inflammation areas of CSCC were not significantly higher than those in the non-cancer samples except for LGALS9 and IDO1. Stronger signals of CD56+ NK cells and immature dendritic cells are found in the hypermetabolic tumor areas, while more eosinophils, immature B cells, and Treg cells are found in the hypometabolic tumor areas. Moreover, a cluster of cancer-associated fibroblasts (CAFs) are identified around some tumors, which highly expressed ACTA2, POSTN, ITGB4, and FAP. The CAFs might support the growth and metastasis of tumors by inhibiting lymphocyte infiltration and remodeling the tumor extracellular matrix. Furthermore, CAFs are associated with poorer survival probability in CSCC patients and might be present in a small fraction (∼20%) of advanced cancer patients. Collectively, these findings might enhance understanding of the CSCC immunological microenvironment and shed some light on the treatment of advanced CSCC.
High throughput hemogram of T cells using digital holographic microscopy and deep learning
Authors: Gupta Roopam K. , Hempler Nils , Malcolm Graeme P. A. , Dholakia Kishan , Powis Simon J. 
Published: December 2021

AbstractT cells of the adaptive immune system provide effective protection to the human body against numerous pathogenic challenges. Current labelling methods of detecting these cells, such as flow cytometry or magnetic bead labelling, are time consuming and expensive. To overcome these limitations, the label-free method of digital holographic microscopy (DHM) combined with deep learning has recently been introduced which is both time and cost effective. In this study, we demonstrate the application of digital holographic microscopy with deep learning to classify the key CD4+and CD8+T cell subsets. We show that combining DHM of varying fields of view, with deep learning, can potentially achieve a classification throughput rate of 78,000 cells per second with an accuracy of 76.2% for these morphologically similar cells. This throughput rate is 100 times faster than the previous studies and proves to be an effective replacement for labelling methods.
Artificial intelligence: a systematic review of methods and applications in hospitality and tourism
Authors: Doborjeh Zohreh , Hemmington Nigel , Doborjeh Maryam , Kasabov Nikola 
Published: December 2021

Purpose
Several review articles have been published within the Artificial Intelligence (AI) literature that have explored a range of applications within the tourism and hospitality sectors. However, how efficiently the applied AI methods and algorithms have performed with respect to the type of applications and the multimodal sets of data domains have not yet been reviewed. Therefore, this paper aims to review and analyse the established AI methods in hospitality/tourism, ranging from data modelling for demand forecasting, tourism destination and behaviour pattern to enhanced customer service and experience.

Design/methodology/approach
The approach was to systematically review the relationship between AI methods and hospitality/tourism through a comprehensive literature review of papers published between 2010 and 2021. In total, 146 articles were identified and then critically analysed through content analysis into themes, including “AI methods” and “AI applications”.

Findings
The review discovered new knowledge in identifying AI methods concerning the settings and available multimodal data sets in hospitality and tourism. Moreover, AI applications fostering the tourism/hospitality industries were identified. It also proposes novel personalised AI modelling development for smart tourism platforms to precisely predict tourism choice behaviour patterns.

Practical implications
This review paper offers researchers and practitioners a broad understanding of the proper selection of AI methods that can potentially improve decision-making and decision-support in the tourism/hospitality industries.

Originality/value
This paper contributes to the tourism/hospitality literature with an interdisciplinary approach that reflects on theoretical/practical developments for data collection, data analysis and data modelling using AI-driven technology.
Tone, readability and financial risk: the case of GCC banks
Authors: Hassan Mostafa Kamal , Abu-Abbas Bassam , Kamel Hany 
Published: December 2021

PurposeThe authors investigate the impact of disclosure tones and financial risk on the readability of annual reports in the banking sector. The authors also examine the moderating effect of banks' financial risk on the tone–readability relationship.Design/methodology/approachThis study relies on the agency theory and the social psychology theory to formulate its testable hypotheses and explain the empirical findings. It uses a sample of 390 bank-year observations from banks listed in the Gulf Cooperation Council (GCC) Stock Exchanges during the period 2014–2019. It also employs random effect regressions to analyze the data and to examine the reverse causality/endogeneity in order to obtain robust findings.FindingsThis study’s results demonstrate that easy (difficult) to read annual reports is significantly associated with positive (negative) tone. Bank managers characterized as “too positive/optimistic” and banks with higher financial risks publish less readable annual reports. The results also show that the interaction between negative tone and a bank's financial risk is inversely associated with reading difficulty, indicating that managers prepare easy text to clarify causes of their banks’ high risks, yet they communicate this easy text with a negative tone that reflects their feelings/emotions towards the financial risks of their banks.Practical implicationsThis study’s findings call for the use of a plain English text that bears a neutral tone and urge financial analysts to go beyond the financial aspects of annual reports. They also stimulate policymakers to draft policies, which ensure the presence of audit committee members who possess a broad expertise to uncover the linguistic issues embedded in the annual reports.Originality/valueTo the best of the authors' knowledge, this is the first study dedicated to exploring the tone–readability association in the GCC's banking sector.
Cameroon’s special criminal court: an appraisal of its first decade of existence
Authors: Agbor Avitus Agbor 
Published: December 2021

Purpose
In total, 10 years since the establishment of the Special Criminal Court (SCC) in Cameroon to deal with a specific kind of corruption, one may wonder whether any achievements have been made so far in fulfilling its mandate and also assuaging the tense and toxic perception that the Court was established as an arsenal to witch-hunt political opponents. This study aims to look into the work done so far in this regard, and makes an assessment as to whether any accomplishments have been made in the first decade of its establishment.

Design/methodology/approach
This paper takes an evidence-based approach in seeking answers to what accomplishments, if any, have been made by the Court, explores the notion of corruption within Cameroon’s legislative and institutional landscape prior to the establishment of the Court and looks into the profiles of those who have been indicted by the SCC for that crime; the amounts that were misappropriated and for which they were convicted; the sentences imposed. It identifies some outstanding cases: where the amounts misappropriated exceeded a threshold and asks the question of what made it possible for these individuals to misappropriate such huge sums of money?

Findings
The inconsistencies and irrationality in the sentencing are a few findings made. Added to those is the timing of the establishment of the Court which, as most have perceived, is a political witch-hunting aimed at bringing credibility to a failed regime, as well as deal with a few political “irresponsibles” who were once the president’s buddies.

Research limitations/implications
This research unravels key insights into the functioning of the SCC. It advances the knowledge thereon and adds to the literature on corruption in Cameroon.

Practical implications
The establishment of the SCC is commendable. However, as it deals with but a particular kind of corruption, it might be necessary to rethink the need of additional institutional mechanisms that have specialized jurisdiction to deal with the different kinds of corruption in Cameroon.

Social implications
The paper highlights the entrenched nature of corruption in the social fabrics of Cameroonian society, and exposes the need for a much holistic approach in dealing with corruption, as the SCC offers but one institutional mechanism toward that direction.

Originality/value
This paper, given the issues discussed therein, and considering the dearth of literature on the topic, advances the literature on the SCC in particular and the problem of endemic corruption in Cameroon in general.
Negotiating without the victim state: the exclusiveness of anticorruption settlements
Authors: Capus Nadja , Brodersen Kei Hannah 
Published: December 2021

Purpose
Corporate foreign bribery can have devastating consequences on communities and states. Over the past decade, there have been several promising developments, both national and international, that might increase the chances of victim states to receive remediation for the harm they suffered from foreign bribery. In particular, awareness has risen that victim states must be considered and new innovative items have been added to the toolbox of prosecutors in the fight against corruption that is assumed to also improve victim states’ standing in these procedures. This study aims to assess whether indeed victim states receive compensation through these novel procedures.

Design/methodology/approach
This study uses the three case studies of Switzerland, France and England and Wales for a comprehensive empirical and normative analysis of settlement agreements between defendants and prosecution authorities and of court jurisprudence.

Findings
This study shows that although de jure, it seems warranted to order the payment of remedies to victim states within domestic criminal proceedings, in practice, this rarely happens. A number of legal and practical obstacles account for this situation. This study, therefore, calls for the formulation of international guidelines containing the obligation to inform victim states of ongoing criminal proceedings on corporate foreign bribery, and guidance on how to identify the victim of this crime, as well as the damage caused.

Originality/value
This is the first contribution to verify whether claims that settlement agreements, recently introduced in England and Wales and France (and similar procedures are available in Switzerland), are beneficial for victim states in their quest to receive compensation. As this study shows that this is – not yet – the case in practice, this study proposes solutions that could lead the way for remediation of the harm caused by corporate corruption – and thereby, ultimately, to a more just outcome.
Management accounting tools for failure prevention and risk management in the context of Indian innovative start-ups: a contingency theory approach
Authors: Krishnan (Retd.) Cdr S. Navaneetha , Ganesh L.S. , Rajendran C. 
Published: December 2021

Purpose
This paper aims to analyse various failures that Indian innovative start-ups (ISs) are exposed to and proposes interventions from management accounting tools (MATs) that can tackle their failure-causing risks. This paper justifies the applicability of contingency theory (CT) for applying MATs for failure prevention and risk management.

Design/methodology/approach
This paper uses multimethod research while undertaking two sequential studies. The methods include a Survey via semi-structured interviews of 51 specialists and media reports and the Delphi method.

Findings
Reasons for the failures of Indian ISs have been identified and grouped based on eight broad underlying risk factors. Appropriate MATs relevant to ISs have been identified and examined by relating them with the risk factors underlying failure. Applicability of CT is shown while using the MATs for failure prevention and risk management of ISs.

Research limitations/implications
This study is limited to the Indian context. Empirical validation of the applicability of MATs for each type of failure along the lifecycle stages of ISs needs to be undertaken.

Practical implications
Founders/owners of ISs can use this conceptual framework to tackle the risks underlying the failure of their firms. Policymakers can introduce appropriate policies to enhance the survival of ISs. Researchers can further explore the application of CT for failure prevention and risk management of ISs.

Originality/value
A conceptual framework has been developed relating failure-causing risk factors relevant to ISs and appropriate MATs, which justifies the applicability of CT.
The fake news effect: what does it mean for consumer behavioral intentions towards brands?
Authors: Sharif Aruba , Awan Tahir Mumtaz , Paracha Osman Sadiq 
Published: December 2021

Purpose
This study aims to understand how fake news can cause an impact on consumer behavioral intentions in today’s era when fake news is prevalent and common. Brands have not only faced reputational losses but also got a dip in their share prices and sales, which affected their financial standing. Hence, it is significant for brands to understand the impact of fake news on behavioral intentions and to strategize to manage the impact.

Design/methodology/approach
This study uses several branding and marketing concepts such as brand experience, brand trust, brand credibility, consumer behavioral intentions along with variables suggested by Elaboration Likelihood Model and Heuristic Systematic Model such as personal relevance/involvement. For fake news, news truthfulness, news credibility and source credibility are used.

Findings
The results of this study shows that positive brand experience, brand trust, brand credibility help in creating positive behavioral intentions for brands. This study shows that brands focusing on providing positive brand experience have a stronger brand trust and credibility and are affected less by fake news than those brands which do not emphasize on these factors.

Practical implications
This paper can assist brand managers in understanding the impact fake news can have on behavioral intentions of consumers. The managers can strategize such that the fake news affects their brands the least.

Originality/value
The authors in this paper attempt to fill in the gap in literature, which is to study how the fake news impacts the brands considering the credibility, trust and experience they establish with their customers. The existing literature discusses the generation and dissemination of fake news on social media and its impact on political scenarios and personalities. Also, studies explain the impact of fake news on the financial position of brands, but marketing facets are not tested empirically.