bluuebunny/crossref_metadata_2025 huggingface dataset:
ADAD2 regulates heterochromatin in meiotic and post-meiotic male germ cells via translation of MDC1
Authors: Chukrallah Lauren G. , Badrinath Aditi , Vittor Gabrielle G. , Snyder Elizabeth M.
Published: July 2021

Male germ cells establish a unique heterochromatin domain, the XY-body, early in meiosis. How this domain is maintained through the end of meiosis and into post-meiotic germ cell differentiation is poorly understood. ADAD2 is a late meiotic male germ cell specific RNA binding protein, loss of which leads to post-meiotic germ cell defects. Analysis of ribosome association in Adad2 mutants revealed defective translation of Mdc1, a key regulator of XY-body formation, late in meiosis. As a result, Adad2 mutants show normal establishment but failed maintenance of the XY-body. XY-body defects are concurrent with abnormal autosomal heterochromatin and ultimately lead to severely perturbed post-meiotic germ cell heterochromatin and cell death. These findings highlight the requirement of ADAD2 for Mdc1 translation, the role of MDC1 in maintaining meiotic male germ cell heterochromatin, and the importance of late meiotic heterochromatin for normal post-meiotic germ cell differentiation.

Chukrallah et al. demonstrate ADAD2 is required for normal meiotic heterochromatin in male germ cells and loss leads to post-meiotic cell death defining ADAD2 as a heterochromatin maintenance factor.
An Oscillatory Mechanism for Multi-level Storage in Short-term Memory
Authors: Champion Kathleen P. , Gozel Olivia , Lankow Benjamin S. , Ermentrout G. Bard , Goldman Mark S.
Published: July 2021

Oscillatory activity is commonly observed during the maintenance of information in short-term memory, but its role remains unclear. Non-oscillatory models of short-term memory storage are able to encode stimulus identity through their spatial patterns of activity, but are typically limited to either an all-or-none representation of stimulus amplitude or exhibit a biologically implausible exact-tuning condition. Here, we demonstrate a simple phase-locking mechanism by which oscillatory input enables a circuit to generate persistent or sequential activity patterns that encode information not only in their location but also in their discretely graded amplitudes.

Significance

A core observation in many memory systems and tasks is the presence of oscillations during memory maintenance. Here, we demonstrate a mechanism for the accumulation and storage of information in short-term memory in which oscillatory activity enables a solution to long-standing challenges in modeling the persistent neural activity underlying working memory. These challenges include the ability to encode information with low firing rates, multi-level storage of stimulus amplitude without extreme fine tuning, and multi-level storage of information in sequential activity. Altogether, this work proposes a new class of models for the storage of information in working memory, a new potential role for brain oscillations, and a novel dynamical mechanism for multi-stability.
AnchorWave: sensitive alignment of genomes with high diversity, structural polymorphism and whole-genome duplication variation
Authors: Song Baoxing , Marco-Sola Santiago , Moreto Miquel , Johnson Lynn , Buckler Edward S. , Stitzer Michelle C.
Published: July 2021

Millions of species are currently being sequenced and their genomes are being compared. Many of them have more complex genomes than model systems and raised novel challenges for genome alignment. Widely used local alignment strategies often produce limited or incongruous results when applied to genomes with dispersed repeats, long indels, and highly diverse sequences. Moreover, alignment using many-to-many or reciprocal best hit approaches conflicts with well-studied patterns between species with different rounds of whole-genome duplication or polyploidy levels. Here we introduce AnchorWave, which performs whole-genome duplication informed collinear anchor identification between genomes and performs base-pair resolution global alignments for collinear blocks using the wavefront algorithm and a 2-piece affine gap cost strategy. This strategy enables AnchorWave to precisely identify multi-kilobase indels generated by transposable element (TE) presence/absence variants (PAVs). When aligning two maize genomes, AnchorWave successfully recalled 87% of previously reported TE PAVs between two maize lines. By contrast, other genome alignment tools showed almost zero power for TE PAV recall. AnchorWave precisely aligns up to three times more of the genome than the closest competitive approach, when comparing diverse genomes. Moreover, AnchorWave recalls transcription factor binding sites (TFBSs) at a rate of 1.05-74.85 fold higher than other tools, while with significantly lower false positive alignments. AnchorWave shows obvious improvement when applied to genomes with dispersed repeats, active transposable elements, high sequence diversity and whole-genome duplication variation.

Significance statement

One fundamental analysis needed to interpret genome assemblies is genome alignment. Yet, accurately aligning regulatory and transposon regions outside of genes remains challenging. We introduce AnchorWave, which implements a genome duplication informed longest path algorithm to identify collinear regions and performs base-pair resolved, end-to-end alignment for collinear blocks using an efficient 2-piece affine gap cost strategy. AnchorWave improves alignment of partially synthetic and real genomes under a number of scenarios: genomes with high similarity, large genomes with high TE activity, genomes with many inversions, and alignments between species with deeper evolutionary divergence and different whole-genome duplication histories. Potential use cases for the method include genome comparison for evolutionary analysis of non-genic sequences and population genetics of taxa with complex genomes.
Investigating molecular crowding during cell division in budding yeast with FRET
Authors: Lecinski Sarah , Shepherd Jack W , Frame Lewis , Hayton Imogen , MacDonald Chris , Leake Mark C
Published: July 2021

Cell division, aging, and stress recovery triggers spatial reorganization of cellular components in the cytoplasm, including membrane bound organelles, with molecular changes in their compositions and structures. However, it is not clear how these events are coordinated and how they integrate with regulation of molecular crowding. We use the budding yeastSaccharomyces cerevisiaeas a model system to study these questions using recent progress in optical fluorescence microscopy and crowding sensing probe technology. We used a Förster Resonance Energy Transfer (FRET) based sensor, illuminated by confocal microscopy for high throughput analyses and Slimfield microscopy for single-molecule resolution, to quantify molecular crowding. We determine crowding in response to cellular growth of both mother and daughter cells, in addition to osmotic stress, and reveal hot spots of crowding across the bud neck in the burgeoning daughter cell. This crowding might be rationalized by the packing of inherited material, like the vacuole, from mother cells. We discuss recent advances in understanding the role of crowding in cellular regulation and key current challenges and conclude by presenting our recent advances in optimizing FRET-based measurements of crowding whilst simultaneously imaging a third color, which can be used as a marker that labels organelle membranes. Our approaches can be combined with synchronised cell populations to increase experimental throughput and correlate molecular crowding information with different stages in the cell cycle.
SMGen: A generator of synthetic models of biochemical reaction networks
Authors: Riva Simone G. , Cazzaniga Paolo , Nobile Marco S. , Spolaor Simone , Rundo Leonardo , Besozzi Daniela , Tangherloni Andrea
Published: July 2021

Several software tools for the simulation and analysis of biochemical reaction networks have been developed in the last decades; however, assessing and comparing their computational performance in executing the typical tasks of Computational Systems Biology can be limited by the lack of a standardized benchmarking approach. To overcome these limitations, we propose here a novel tool, named SMGen, designed to automatically generate synthetic models of reaction networks that, by construction, are characterized by both features (e.g., system connectivity, reaction discreteness) and non trivial emergent dynamics of real biochemical networks. The generation of synthetic models in SMGen is based on the definition of an undirected graph consisting of a single connected component, which generally results in a computationally demanding task. To avoid any burden in the execution time, SMGen exploits a Main-Worker paradigm to speed up the overall process. SMGen is also provided with a user-friendly Graphical User Interface that allows the user to easily set up all the parameters required to generate a set of synthetic models with any user-defined number of reactions and species. We analysed the computational performance of SMGen by generating batches of symmetric and asymmetric Reaction-based Models (RBMs) of increasing size, showing how a different number of reactions and/or species affects the generation time. Our results show that when the number of reactions is higher than the number of species, SMGen has to identify and correct high numbers of errors during the creation process of the RBMs, a circumstance that increases the overall running time. Still, SMGen can create synthetic models with 512 species and reactions in less than 7 seconds. The open-source code of SMGen is available on GitLab:https://gitlab.com/sgr34/smgen.
Training a spiking neuronal network model of visual-motor cortex to play a virtual racket-ball game using reinforcement learning
Authors: Anwar Haroon , Caby Simon , Dura-Bernal Salvador , D’Onofrio David , Hasegan Daniel , Deible Matt , Grunblatt Sara , Chadderdon George L , Kerr Cliff C , Lakatos Peter , Lytton William W , Hazan Hananel , Neymotin Samuel A
Published: July 2021

Recent models of spiking neuronal networks have been trained to perform behaviors in static environments using a variety of learning rules, with varying degrees of biological realism. Most of these models have not been tested in dynamic visual environments where models must make predictions on future states and adjust their behavior accordingly. The models using these learning rules are often treated as black boxes, with little analysis on circuit architectures and learning mechanisms supporting optimal performance.

Here we developed visual/motor spiking neuronal network models and trained them to play a virtual racket-ball game using several reinforcement learning algorithms inspired by the dopaminergic reward system. We systematically investigated how different architectures and circuit-motifs (feed-forward, recurrent, feedback) contributed to learning and performance. We also developed a new biologically-inspired learning rule that significantly enhanced performance, while reducing training time.

Our models included visual areas encoding game inputs and relaying the information to motor areas, which used this information to learn to move the racket to hit the ball. Neurons in the early visual area relayed information encoding object location and motion direction across the network. Neuronal association areas encoded spatial relationships between objects in the visual scene. Motor populations received inputs from visual and association areas representing the dorsal pathway. Two populations of motor neurons generated commands to move the racket up or down. Model-generated actions updated the environment and triggered reward or punishment signals that adjusted synaptic weights so that the models could learn which actions led to reward.

Here we demonstrate that our biologically-plausible learning rules were effective in training spiking neuronal network models to solve problems in dynamic environments. We used our models to dissect the circuit architectures and learning rules most effective for learning. Our model shows that learning mechanisms involving different neural circuits produce similar performance in sensory-motor tasks. In biological networks, all learning mechanisms may complement one another, accelerating the learning capabilities of animals. Furthermore, this also highlights the resilience and redundancy in biological systems.
A sequence-based global map of regulatory activity for deciphering human genetics
Authors: Chen Kathleen M. , Wong Aaron K. , Troyanskaya Olga G. , Zhou Jian
Published: July 2021

Sequence is at the basis of how the genome shapes chromatin organization, regulates gene expression, and impacts traits and diseases. Epigenomic profiling efforts have enabled large-scale identification of regulatory elements, yet we still lack a sequence-based map to systematically identify regulatory activities from any sequence, which is necessary for predicting the effects of any variant on these activities. We address this challenge with Sei, a new framework for integrating human genetics data with sequence information to discover the regulatory basis of traits and diseases. Our framework systematically learns a vocabulary for the regulatory activities of sequences, which we call sequence classes, using a new deep learning model that predicts a compendium of 21,907 chromatin profiles across >1,300 cell lines and tissues, the most comprehensive to-date. Sequence classes allow for a global view of sequence and variant effects by quantifying diverse regulatory activities, such as loss or gain of cell-type-specific enhancer function. We show that sequence class predictions are supported by experimental data, including tissue-specific gene expression, expression QTLs, and evolutionary constraints based on population allele frequencies. Finally, we applied our framework to human genetics data. Sequence classes uniquely provide a non-overlapping partitioning of GWAS heritability by tissue-specific regulatory activity categories, which we use to characterize the regulatory architecture of 47 traits and diseases from UK Biobank. Furthermore, the predicted loss or gain of sequence class activities suggest specific mechanistic hypotheses for individual regulatory pathogenic mutations. We provide this framework as a resource to further elucidate the sequence basis of human health and disease.
Non-coding circular RNAs repertoire and expression profile during Brassica rapa pollen development
Authors: Babaei Saeid , Singh Mohan B. , Bhalla Prem L
Published: July 2021

Circular RNAs (circRNAs) are covalently closed long non-coding RNA (lncRNA) molecules generated by the back-splicing of exons from linear precursor mRNAs. Though linear lncRNAs have been shown to play important regulatory roles in diverse biological and developmental processes, little is known about the role of their circular counterparts. In this study, we have performed high-throughput RNA sequencing to delineate the expression profile and potential function of circRNAs during the five stages of pollen development in Brassica rapa. A total of 1180 circRNAs were detected in pollen development, of which 367 showed stage-specific expression patterns. Functional enrichment and metabolic pathway analysis showed that the parent genes of circRNAs were mainly involved in pollen-related molecular and biological processes such as mitotic and meiosis cell division, DNA processes, protein synthesis, protein modification, and polysaccharide biosynthesis. Moreover, by predicting the circRNA-miRNA network from our differentially expressed circRNAs, we found 88 circRNAs with potential miRNA binding sites suggesting their role in post-transcriptional regulation of the genes. Finally, we confirmed the back-splicing sites of 9 randomly selected circRNAS using divergent primers and Sanger sequencing. Our study presents the first systematic analysis of circular RNAs during pollen development and forms the basis of future studies for unlocking complex gene regulatory networks underpinning reproduction in flowering plants.
Direct and indirect interactions promote complexes of the lipoprotein LbcA, the CtpA protease and its substrates, and other cell wall proteins in Pseudomonas aeruginosa
Authors: Chakraborty Dolonchapa , Darwin Andrew J.
Published: July 2021

The Pseudomonas aeruginosa lipoprotein LbcA was discovered because it copurified with and promoted the activity of CtpA, a carboxyl-terminal processing protease (CTP) required for type III secretion system function, and for virulence in a mouse model of acute pneumonia. In this study we explored the role of LbcA by determining its effect on the proteome and its participation in protein complexes. lbcA and ctpA null mutations had strikingly similar effects on the proteome, suggesting that facilitating CtpA might be the most impactful role of LbcA in the bacterial cell. Independent complexes containing LbcA and CtpA, or LbcA and substrate, were isolated from P. aeruginosa cells, indicating that LbcA facilitates proteolysis by recruiting the protease and its substrates independently. An unbiased examination of proteins that copurified with LbcA revealed an enrichment for proteins associated with the cell wall. One of these copurification partners was found to be a new CtpA substrate, and the first substrate that is not a peptidoglycan hydrolase. Many of the other LbcA copurification partners are known or predicted peptidoglycan hydrolases. However, some of these LbcA copurification partners were not cleaved by CtpA, and an in vitro assay revealed that while CtpA and all of its substrates bound to LbcA directly, these non-substrates did not. Subsequent experiments suggested that the non substrates might co-purify with LbcA by participating in multi-enzyme complexes containing LbcA-binding CtpA substrates.

IMPORTANCE

Carboxyl-terminal processing proteases (CTPs) are widely conserved and associated with the virulence of several bacteria, including CtpA in Pseudomonas aeruginosa. CtpA copurifies with the uncharacterized lipoprotein, LbcA. This study shows that the most impactful role of LbcA might be to promote CtpA-dependent proteolysis, and that it achieves this as a scaffold for CtpA and its substrates. It also reveals that LbcA copurification partners are enriched for cell wall-associated proteins, one of which is a novel CtpA substrate. Some of the other LbcA copurification partners are not cleaved by CtpA, but might copurify with LbcA because they participate in multi-enzyme complexes containing CtpA substrates. These findings are important, given the links between CTPs, their associated proteins, peptidoglycan remodeling, and virulence.
Long- and short-range order in the Ni52Co2Fe20Ga26 ferromagnetic Heusler alloy
Authors: Macovei Dan , Tolea Felicia
Published: July 2021

The crystalline structure and Fe local environment in a Co-doped Ni–Fe–Ga Heusler alloy, prepared by the melt-spinning technique, were investigated by X-ray diffraction (XRD) and EXAFS at room and low temperatures. The characteristic temperatures of the austenite–martensite phase transitions were determined by differential scanning calorimetry via cooling and heating cycles of the alloy ribbons. As shown by room-temperature XRD, the austenitic phase of the alloy has the chemically ordered L21 Heusler structure. This was confirmed by EXAFS, although this technique was not able to conclusively distinguish between the L21 and B2 structures of the austenite for the analyzed alloy. The low-temperature martensitic phase and its structural evolution towards austenite with increasing temperature were studied by high-energy X-ray diffraction, which evinced the martensite modulation. However, the Fe environment could be fitted by EXAFS with the tetragonal L10 structure of the non-modulated martensite. This proves that the martensite modulation has structural effects on a long-range scale, without significant changes in the short-range order around the atoms. The changes in the local structure around iron on martensitic transformation were correlated with changes in the electronic structure, described by XANES spectroscopy at the Fe K edge.
Locked down and drinking? Are more people self-identifying as having mental health difficulties alongside their drinking via an online platform?
Authors: Calcan Angela , Holmes Mark
Published: July 2021

Purpose

The purpose of this paper is to offer a viewpoint on the impact that the COVID-19 pandemic has had on people’s engagement with an online alcohol service in the UK. This paper examines whether self-reported mental health concerns increased during the pandemic compared to pre-pandemic times.

Design/methodology/approach

A comparison was made between service data captured in one contract area – West Sussex, England – pre-pandemic (April 2019 to March 2020) and during pandemic (April 2020 to March 2021).

Findings

Self-reported mental health treatment needs increased during the pandemic period (71.2% of presentations compared to 50% pre-pandemic) via the online coaching service. Male referrals increased by 74% during the pandemic period compared to the previous year. Female referrals decreased by 4% in the same time period. Feelings of shame and guilt as well as loss of a confidential space to engage in online interventions were common concerns reported by service users.

Research limitations/implications

Research limitations include the relatively small sample size, the sample comprised of self-referred treatment seeking clients, and there was no control group. All data collected is self-report therefore subjective and not necessarily meeting diagnostic criteria.

Practical implications

Of note was the impact of the pandemic on women and their reduced access to the online service during the pandemic. Commissioners and services must adapt their service design and delivery alongside the new “normal” way of living and working. Routine screening of mental health and alcohol use are recommended.

Originality/value

This paper offers insight from an established online/digital service and the impact of the pandemic on people’s engagement with the service.
Supply Chain Management at Beautiful Bags
Authors: Goldberg Rebecca , Kraft Tim , Weiss Elliott , Wight Oliver
Published: July 2021

Joe Smith, senior director of merchandise management at Beautiful Bags (BB), was about to place a large order for the upcoming winter season. He had to decide how many pieces he should order of each product. But another big question whether BB should source the product from its domestic manufacturing facility, its Chinese suppliers, or some combination of the two given the timing needs, labor costs, minimum order requirements, and BB's expanding product assortment?
Psychometric properties of the revised Urdu version dyadic adjustment scale for evaluating marital relationship quality between madrassa and Non-Madrassa married women
Authors: Naeem Bushra , Aqeel Muhammad , Maqsood Aneela , Yousaf Ishrat , Ehsan Saima
Published: July 2021

Purpose

This study aims to explore the indigenous needs of married women in Pakistan due to the public health challenges they face due to marital conflict. The research focuses on investigating psychometric properties and cross-cultural validation of the revised dyadic adjustment scale’s (RDAS) Urdu translated version to assess marital relationship quality between married madrassa and non-madrassa women. The study examines empirically validated two-factor model (RDAS) between married madrassa and non-madrassa women (Busby et al., 1995; Hollist et al., 2012; Isanezhad et al., 2012; Christensen et al., 2006) and (Bayraktaroglu and Cakici, 2017). These studies approach including consensus, satisfaction and cohesion.

Design/methodology/approach

The investigators executed the study into two phases: a pilot test and the main survey.

Findings

The pilot study's findings specified that the Urdu translated version of the revised DAS indicated a decent internal consistency (a = 0.70). The overall revised DAS maintained a stronger test-retest correlation and tested it over 15 days (r = 0.95). The main study recorded 300 respondents' responses from madrassa and non-madrassa married women using a purposive sampling approach and recruited them from the locality of various madrassas and housing societies of Islamabad, Azad Kashmir and Rawalpindi, Pakistan. The study findings showed higher intercorrelations between total and subscales of the revised DAS. It further compared the groups with a multi-group confirmatory factor analysis (CFA) method and examined the revised DAS structure in married madrassa and non-madrassa women.

Practical implications

This study contributes to scientific knowledge and helps develop and validate indigenous cross-cultural instruments to examine marital life quality. It offers practical and reliable information about Pakistani couples' emotional attachment and marriage adjustment issues.

Originality/value

The study applied a three-factor solution, and it demonstrated a robust factorial validity in the context of Pakistani culture, which is a novel contribution to the literature.
Impact of disruptions in agri-food supply chain due to COVID-19 pandemic: contextualised resilience framework to achieve operational excellence
Authors: Mishra Ruchi , Singh Rajesh Kumar , Subramanian Nachiappan
Published: July 2021

Purpose

The present study aims to assess the role of supply chain resilience as an operational excellence approach to deal with disruptions caused by coronavirus pandemic in the food supply chain of an agri-food supply firm.

Design/methodology/approach

The case study method was used to analyse the disruptions faced by the agricultural food supply chain during the pandemic. The study applies a dynamic capability theory as a foundation to develop a contextualised resilience framework for agri-food supply chain to achieve operational excellence. The case has been analysed by using situation-actor-process (SAP) and learning-action-performance (LAP) framework.

Findings

The SAP aspect of framework points that the flexibility amongst actors for a resilient agriculture supply chain worsened due to the lockdown measures post COVID-19. The LAP aspect of framework suggests how resilience can be built at the supply, demand and logistics end through various proactive and reactive practices such as collaboration, coordination, ICT and ground-level inputs. Lack of commitment and inadequate support from top management towards supply chain resilience are also observed as significant challenges to maintain operational excellence during the pandemic.

Research limitations/implications

One of the major implications of the study is that a mix of capabilities rather than a single capability can be the most appropriate way for making the supply chain resilient to maintain operational excellence during the pandemic. However, the sources of disruptions need to be duly recognised to derive the best-contextualised resilience framework for agri-food supply chains.

Originality/value

The development of a contextualised research framework as well as research propositions for analysing supply chain resilience are the major contribution of this study.
Challenges in the implementation of lean manufacturing in the wood and furniture industry
Authors: Abu Falah , Saman Muhamad Zameri Mat , Garza-Reyes Jose Arturo , Gholami Hamed , Zakuan Norhayati
Published: July 2021

Purpose

This study analyses the challenges in implementing lean manufacturing (LM) in the wood and furniture industry. In order to facilitate the smooth implementation of LM practices in this industry, the challenges in terms of its deployment need to be analysed and observed.

Design/methodology/approach

Realizing this importance, this study proposes a model, using PLS-SEM, which focusses on dealing with the challenges faced in the implementation of lean in the wood and furniture industry. The model consists of ten challenges that were determined based on a survey involving 46 SMEs companies in Malaysia.

Findings

The findings revealed that the implementation of LM is significantly affected by three main issues, namely: knowledge, resources and culture and human attitude. Furthermore, the analyses also highlighted four dominant challenges which are related to culture and human attitude issues – lack of employee commitment, lack of senior management's interest and support, difficult to implement, and LM is viewed as “current trend”. Overall, the ability to deal with the challenges involving factors of knowledge and culture and human attitude determines the success of LM implementation, especially in companies that have limited resources.

Practical implications

This study would help wood and furniture SMEs, government agencies, professional bodies and academics to better understand the challenges when implementing LM practices.

Originality/value

Overall, this study aims at investigating the relationships between the three challenges to better promote LM in the scope under study. Therefore, several activities were proposed to overcome the abovementioned challenges and subsequently contribute to the current body of knowledge.
The determinants of capitalisation rates: evidence from the US real estate markets
Authors: Larriva Matt , Linneman Peter
Published: July 2021

Purpose

Establishing the strength of a novel variable–mortgage debt as a fraction of US gross domestic product (GDP)–on forecasting capitalisation rates in both the US office and multifamily sectors.

Design/methodology/approach

The authors specify a vector error correction model (VECM) to the data. VECM are used to address the nonstationarity issues of financial variables while maintaining the information embedded in the levels of the data, as opposed to their differences. The cap rate series used are from Green Street Advisors and represent transaction cap rates which avoids the problem of artificial smoothness found in appraisal-based cap rates.

Findings

Using a VECM specified with the novel variable, unemployment and past cap rates contains enough information to produce more robust forecasts than the traditional variables (return expectations and risk premiums). The method is robust both in and out of sample.

Practical implications

This has direct implications for governmental policy, offering a path to real estate price stability and growth through mortgage access–functions largely influenced by the Fed and the quasi-federal agencies Fannie Mae and Freddie Mac. It also offers a timely alternative to interest rate-based forecasting models, which are likely to be less useful as interest rates are to be held low for the foreseeable future.

Originality/value

This study offers a new and highly explanatory variable to the literature while being among the only to model either (1) transactional cap rates (versus appraisal) (2) out-of-sample data (versus in-sample) (3) without the use of the traditional variables thought to be integral to cap rate modelling (return expectations and risk premiums).
The missing link between overtourism and post-pandemic tourism. Framing Twitter debate on the Italian tourism crisis
Authors: Pasquinelli Cecilia , Trunfio Mariapina
Published: July 2021

Purpose

This paper aims to exploit existing tourism knowledge to frame the unprecedented pandemic tourism crisis, its key aspects and impacts on the tourism industry. It builds a conceptual bridge and discusses the opportunity to capitalise on the missing link between the pre-COVID overtourism and the post-COVID “undertourism” debates.

Design/methodology/approach

A cross-fertilisation between the overtourism knowledge and the emerging COVID-19 literature stream is proposed and supported by an online media analysis focussing on the Italian tourism debate on Twitter. A text analysis of 2,500 posts helps discuss the conceptual framework.

Findings

The analysed Twitter debate prioritised socio-economic impacts, regulative actions and the recovery approach, representing government as the pivotal actor to overcome the pandemic crisis. An integrative interpretative framework results from this research, opening three areas of inquiry, such as the recovery–reform continuum, managerial approaches beyond regulative frames of action and a critical sizing of digital technologies deployment.

Research limitations/implications

Samples with different geographical and temporal coverage may provide further and multifaceted insights into the emerging tourism online media debate.

Originality/value

An original conceptualisation counter-intuitively frames post-pandemic tourism scenarios. Additional elements of originality are the online media analysis contributing to the emerging COVID-19 agenda and the use of Twitter social platform to investigate the tourism debate.
CFO attributes and accounting conservatism: evidence from Malaysia
Authors: Ismail Ismaanzira , Shafie Rohami , Ku Ismail Ku Nor Izah
Published: July 2021

Purpose

This paper aims to examine whether conditional conservatism is affected by chief financial officer (CFO) attributes as this issue is understudied in Malaysia. Given that CFOs have a direct responsibility for financial reporting, therefore, their individual attributes are important in influencing conservatism in financial reporting.

Design/methodology/approach

This study uses non-financial listed firms in the Main Market of Bursa Malaysia from the years 2016 until 2019.

Findings

The results show that CFOs’ attributes, namely, gender, age, education level and ethnicity, affect earnings conservatism. To test for robustness, the authors use difference-in-difference, propensity score-matching and unconditional conservatism, namely, market-to-book ratio and the authors find the results hold with an exception for age and education level. Further, the effect of these attributes is more profound in non-Big4 audited firms, suggesting that CFO attributes act as a substitute mechanism for lower audit quality.

Originality/value

This study complements existing studies by documenting the first evidence on the significant effects of CFOs’ attributes in influencing accounting conservatism in an emerging country, namely, Malaysia. This is the first paper, to the humble knowledge, that examines CFOs’ attributes on accounting conservatism in Malaysia.
Social media: a blessing or a curse? Voice of owners in the beauty and wellness industry
Authors: Kaur Kulvinder , Kumar Pawan
Published: July 2021

Purpose

The rise in the use of Internet technologies and social media has shifted the marketing practices from offline to online. This study aims to determine the pros and cons of social media marketing in the beauty and wellness industry.

Design/methodology/approach

In-depth interviews were conducted with the owners and marketing executives of beauty and wellness centers to understand the use of popular social media platforms in this industry and their pros and cons.

Findings

The researchers identified eight merits and seven demerits of social media in the beauty and wellness industry. Every respondent is happy and satisfied with social media use, particularly Instagram and Facebook. Irrespective of the demerits, they have shown the intention to increase its usage in the future. The merits override demerits; thus, social media is a blessing for this industry from the owners' perspective.

Research limitations/implications

The research is exploratory and is confined to just one industry. Research implication is that the visual nature of social media makes it a powerful tool for the promotion of the beauty and wellness industry.

Practical implications

The study's findings will be beneficial for small-scale businesses as it will push them to take advantage of this low-cost marketing tool.

Social implications

Social media marketing is helpful for communication and marketing purposes for society.

Originality/value

The beauty and wellness industry remained unfocused by researchers because it is highly unorganized, fragmented and not regulated, yet has huge growth potential. This research will provide a closer look at this industry as well as social media marketing.
Experimental, analytical and numerical, investigation of peak temperature and cooling rate in butt joint weld of mild steel
Authors: Singh Mayur Pratap , Meena Pavan Kumar , Arora Kanwer Singh , Kumar Rajneesh , Shukla Dinesh Kumar
Published: July 2021

Purpose

This paper aims to measure peak temperatures and cooling rates for distinct locations of thermocouples in the butt weld joint of mild steel plates. For experimental measurement of peak temperatures, K-type thermocouples coupled with a data acquisition system were used at predetermined locations. Thereafter, Rosenthal’s analytical models for thin two-dimensional (2D) and thick three-dimensional (3D) plates were adopted to predict peak temperatures for different thermocouple positions. A finite element model (FEM) based on an advanced prescribed temperature approach was adopted to predict time-temperature history for predetermined locations of thermocouples.

Design/methodology/approach

Comparing experimental and Rosenthal analytical models (2D and 3D) findings show that predicted and measured peak temperatures are in close agreement, while cooling rates predicted by analytical models (2D, 3D) show significant variation from measured values. On the other hand, 3D FEM simulation predicted peak temperatures and cooling rates for different thermocouple positions are close to experimental findings.

Findings

The inclusion of filler metal during simulation of welding rightly replicates the real welding situation and improves outcomes of the analysis.

Originality/value

The present study is an original contribution to the field of welding technology.
Ontogenetic trait shifts: Seedlings display high trait variability during early stages of development
Authors: Havrilla Caroline A. , Munson Seth M. , Yackulic Ethan O. , Butterfield Bradley J.
Published: July 2021

Characterizing variation in plant functional traits is often key to understanding community‐level processes and predicting ecosystem responses to environmental change. Trait‐based ecology has focused on interspecific trait variation, but sources and consequences of within‐species ontogenetic trait variation, particularly during early stages of development, remain understudied.

Using a manipulative greenhouse experiment, we investigated trait variation during early stages of seedling development in seven dominant perennial plant species in the western United States. We examined variability in key trait values (i.e. SLA, root:shoot ratio (RSR), specific root length (SRL) and root dry matter content (RDMC)) of 20‐ to 62‐day‐old seedlings grown under low and high levels of water availability. We also compared these to compiled trait databases to assess how representative these readily available data sources are of seedling trait values.

Early seedling trait values shifted greatly during early stages of development and generally differed from average plant trait database values. Trait shifts were greatest in forbs versus grasses. Overall, observed trait shifts suggested a transition from fast‐growing resource acquisitional strategies towards more slow‐growing conservative strategies over time. For example, seedling SLA decreased while RSR and RDMC increased over time.

That seedling trait values aconsistently differed from trait database values indicates that plant trait database values may be poor predictors of seedling trait values. Such mismatches in species trait information could result in inaccurate predictions of community assembly outcomes or incongruities between seedling traits and environmental filters experienced by seedlings during early stages of recruitment in applied settings.

We suggest that additional work is needed to characterize intraspecific trait variation across plant ontogeny, and that this information should be incorporated into studies ranging from understanding early plant growth and survival to evaluating the outcomes of ecological restoration.

A freePlain Language Summarycan be found within the Supporting Information of this article.
Measuring the quality of dental care among privately insured children in the United States
Authors: Choi Sung Eun , Kalenderian Elsbeth , Normand Sharon‐Lise
Published: July 2021

Objective

To examine whether quality of dental care varies by age and over time and whether community‐level characteristics explain these patterns.

Data Source

Deidentified medical and dental claims from a commercial insurer from January 2015 to December 2019.

Study Design

A retrospective cohort study. The primary outcome was a composite quality score, derived from seven dental quality measures (DQMs), with higher values corresponding to better quality. Hierarchical regression models identified person‐ and zip code–level factors associated with the quality.

Data Collection/Extraction Methods

Continuously enrolled US dental insurance beneficiaries younger than 21 years of age.

Principal Findings

Quality was assessed for 4.88 million person‐years covering 1.31 million persons. Overall quality slightly improved over time, mostly driven by substantial improvements among children aged 0–5 years by 0.153 points/year (95% confidence interval [CI]:0.151, 0.156). Quality was poorest and declined over time among adolescents with only 20.5% of DQMs met as compared to 42.6% among aged 0–5 years in 2019. Dental professional shortage, median household income, percentages of African Americans, unemployed, and less‐educated populations at the zip code level were associated with the composite score.

Conclusion

Quality of dental care among adolescents remains low, and place of residence influenced the quality. Increasing the supply of dentists and oral health promotion strategies targeting adolescents and low‐performing localities should be explored.
Online child pornography offender risk assessment using digital forensic artifacts: The need for a hybrid model
Authors: Rogers Marcus K. , Seigfried‐Spellar Kathryn C. , Bates Sienna , Rux Kayla
Published: July 2021

The prevalence of online child pornography is a major societal issue. The criminal justice system has struggled with assessing the risk of individuals involved in online sexual offenses against children, especially when it involves the possession of child pornography. Research suggests there are different categories of offenders involved in this type of behavior (e.g., Online Child Pornography Offenders, Dual Offenders, Contact Offenders), with each category having different motivations, contributing factors, and levels of risk to re‐offend or escalate their criminal behavior to more serious offenses (i.e., collecting pictures to contact offending). Determining the risk that individuals involved in online sexual offenses against children pose to re‐offend or escalate their criminal behavior has been problematic. Traditional sexual offender risk measures have lower predictive validity when dealing with online child pornography offenders. This article discusses the need for a formalized hybrid risk assessment model that combines the current online sex offenses against children risk measures with digital forensics artifact analysis. The evidence derived from digital forensics artifact analysis can supplement the predictive risk factors obtained from these risk assessment tools, thus increasing the reliability and validity of the risk assessment.
High‐throughput dilution‐based growth method enables time‐resolved exo‐metabolomics of Pseudomonas putida and Pseudomonas aeruginosa
Authors: Pedersen Bjarke H. , Gurdo Nicolás , Johansen Helle Krogh , Molin Søren , Nikel Pablo I. , La Rosa Ruggero
Published: July 2021

Understanding metabolism is fundamental to access and harness bacterial physiology. In most bacteria, nutrient utilization is hierarchically optimized according to their energetic potential and their availability in the environment to maximise growth rates. Low‐throughput methods have been largely used to characterize bacterial metabolic profiles. However, in‐depth analysis of large collections of strains across several conditions is challenging since high‐throughput approaches are still limited – especially for non‐traditional hosts. Here, we developed a high‐throughput dilution‐resolved cultivation method for metabolic footprinting of Pseudomonas putida and Pseudomonas aeruginosa. This method was benchmarked against a conventional low‐throughput time‐resolved cultivation approach using either a synthetic culture medium (where a single carbon source is present) for P. putida or a complex nutrient mixture for P. aeruginosa. Dynamic metabolic footprinting, either by sugar quantification or by targeted exo‐metabolomic analyses, revealed overlaps between the bacterial metabolic profiles irrespective of the cultivation strategy, suggesting a certain level of robustness and flexibility of the high‐throughput dilution‐resolved method. Cultivation of P. putida in microtiter plates imposed a metabolic constraint, dependent on oxygen availability, which altered the pattern of secreted metabolites at the level of sugar oxidation. Deep‐well plates, however, constituted an optimal cultivation set‐up yielding consistent and comparable metabolic profiles across conditions and strains. Altogether, the results illustrate the usefulness of this technological advance for high‐throughput analyses of bacterial metabolism for both biotechnological applications and automation purposes.
The potential and practice of arboreal camera trapping
Authors: Moore Jennifer F. , Soanes Kylie , Balbuena Diego , Beirne Christopher , Bowler Mark , Carrasco‐Rueda Farah , Cheyne Susan M. , Coutant Opale , Forget Pierre‐Michel , Haysom Jessica K. , Houlihan Peter R. , Olson Erik R. , Lindshield Stacy , Martin Jonathan , Tobler Mathias , Whitworth Andrew , Gregory Tremaine
Published: July 2021

Arboreal camera trapping is a burgeoning method providing a novel and effective technique to answer research questions across a variety of ecosystems, and it has the capacity to improve our understanding of a wide range of taxa. However, while terrestrial camera trapping has received much attention, there is little guidance for dealing with the unique challenges of working in the arboreal realm.

Our review draws on the expertise of researchers from six continents and the broader literature to investigate the advantages and disadvantages of arboreal camera trapping, and challenges to consider when using this technology. We also include mini‐guides with detailed information on the current arboreal camera trap literature, mounts used to install arboreal cameras, tree climbing pointers and safety tips, methods for deploying cameras without climbing, and tips for managing interference with camera function.

We find that arboreal camera traps have been most commonly used in the study of mammals in forests; however, there is potential for this method to be applied to a broad range of habitats including urban areas, and taxa such as birds, amphibians, invertebrates, and plants. Methods in arboreal camera trapping could be improved by developing a greater understanding of the factors affecting detection of species. The most common challenges of arboreal camera trapping are camera placement and camera site access. These can be overcome by understanding correct camera orientation, managing potential sources of interference in front of cameras, utilizing appropriate cameras mounts and training researchers properly.

Given the benefits and opportunities presented by arboreal camera trapping, it is likely to become an ever‐more popular method of studying arboreal species and systems. The information synthesized in this review provides guidance for future studies to help direct more reliable and robust ecological inferences from arboreal camera trapping.