bluuebunny/crossref_metadata_2025_split huggingface dataset:
HIV-1 Vif gained breadth in APOBEC3G specificity after cross-species transmission of its precursors
Authors: Chesarino Nicholas M. , Emerman Michael 
Published: August 2021

AbstractAPOBEC3G (A3G) is a host-encoded cytidine deaminase that potently restricts retroviruses, such as HIV-1, and depends on its ability to package into virions. As a consequence of this, HIV-1 protein Vif has evolved to antagonize human A3G by targeting it for ubiquitination and subsequent degradation. There is an ancient arms-race between Vif and A3G highlighted by amino acids 128 and 130 in A3G that have evolved under positive selection due to Vif-mediated selective pressure in Old World primates. Nonetheless, not all possible amino acid combinations at these sites have been sampled by nature and it is not clear the evolutionary potential of species to resist Vif antagonism. To explore the evolutionary space of positively selected sites in the Vif-binding region of A3G, we designed a combinatorial mutagenesis screen to introduce all 20 amino acids at sites 128 and 130. Our screen uncovered mutants of A3G with several interesting phenotypes, including loss of stability and resistance of Vif antagonism. However, HIV-1 Vif exhibited remarkable flexibility in antagonizing A3G 128 and 130 mutants, which significantly reduces viable Vif resistance strategies for hominid primates. Importantly, we find that broadened Vif specificity was conferred through Loop 5 adaptations that were required for cross-species adaptation from Old World monkey A3G to hominid A3G. Our evidence suggests that Vif adaptation to novel A3G interfaces during cross-species transmission may train Vif towards broadened specificity that can further facilitate cross-species transmissions and raise the barrier to host resistance.
SEA: Simple Enrichment Analysis of motifs
Authors: Bailey Timothy L. , Grant Charles E. 
Published: August 2021

AbstractMotif enrichment algorithms can identify known sequence motifs that are present to a statistically significant degree in DNA, RNA and protein sequences. Databases of such known motifs exist for DNA- and RNA-binding proteins, as well as for many functional protein motifs. The SEA (“Simple Enrichment Analysis”) algorithm presented here uses a simple, consistent approach for detecting the enrichment of motifs in DNA, RNA or protein sequences, as well as in sequences using user-defined alphabets. SEA can identify known motifs that are enriched in a single set of input sequences, and can also perform differential motif enrichment analysis when presented with an additional set of control sequences. Using in vivo DNA (ChIP-seq) data as input to SEA, and validating motifs with reference motifs derived from in vitro data, we show that SEA is is faster than three widely-used motif enrichment algorithms (AME, CentriMo and Pscan), while delivering comparable accuracy. We also show that, in contrast to other motif enrichment algorithms, SEA reports accurate estimates of statistical significance. SEA is easy to use via its web server at https://meme-suite.org, and is fully integrated with the widely-used MEME Suite of sequence analysis tools, which can be freely downloaded at the same web site for non-commercial use.
Poly(A)-binding protein is an ataxin-2 chaperone that emulsifies biomolecular condensates
Authors: Boeynaems Steven , Dorone Yanniv , Marian Anca , Shabardina Victoria , Huang Guozhong , Kim Garam , Sanyal Anushka , Şen Nesli-Ece , Docampo Roberto , Ruiz-Trillo Iñaki , Lasker Keren , Auburger Georg , Kabashi Edor , Gitler Aaron D. 
Published: August 2021

SUMMARYBiomolecular condensation underlies the biogenesis of an expanding array of membraneless assemblies, including stress granules (SGs) which form under a variety of cellular stresses. Advances have been made in understanding the molecular grammar that dictates the behavior of a few key scaffold proteins that make up these phases but how the partitioning of hundreds of other SG proteins is regulated remains largely unresolved. While investigating the rules that govern the condensation of ataxin-2, a SG protein implicated in neurodegenerative disease, we unexpectedly identified a short 14aa sequence that acts as an ataxin-2 condensation switch and is conserved across the eukaryote lineage. We identify poly(A)-binding proteins as unconventional RNA-dependent chaperones that control this regulatory switch. Our results uncover a hierarchy of cis and trans interactions that fine-tune ataxin-2 condensation and reveal a new molecular function for ancient poly(A)-binding proteins as emulsifiers of biomolecular condensate proteins. These findings may inspire novel approaches to therapeutically target aberrant phases in disease.
An overlapping sliding window and combined features based emotion recognition system for EEG signals
Authors: Garg Shruti , Patro Rahul Kumar , Behera Soumyajit , Tigga Neha Prerna , Pandey Ranjita 
Published: August 2021

PurposeThe purpose of this study is to propose an alternative efficient 3D emotion recognition model for variable-length electroencephalogram (EEG) data.Design/methodology/approachClassical AMIGOS data set which comprises of multimodal records of varying lengths on mood, personality and other physiological aspects on emotional response is used for empirical assessment of the proposed overlapping sliding window (OSW) modelling framework. Two features are extracted using Fourier and Wavelet transforms: normalised band power (NBP) and normalised wavelet energy (NWE), respectively. The arousal, valence and dominance (AVD) emotions are predicted using one-dimension (1D) and two-dimensional (2D) convolution neural network (CNN) for both single and combined features.FindingsThe two-dimensional convolution neural network (2D CNN) outcomes on EEG signals of AMIGOS data set are observed to yield the highest accuracy, that is 96.63%, 95.87% and 96.30% for AVD, respectively, which is evidenced to be at least 6% higher as compared to the other available competitive approaches.Originality/valueThe present work is focussed on the less explored, complex AMIGOS (2018) data set which is imbalanced and of variable length. EEG emotion recognition-based work is widely available on simpler data sets. The following are the challenges of the AMIGOS data set addressed in the present work: handling of tensor form data; proposing an efficient method for generating sufficient equal-length samples corresponding to imbalanced and variable-length data.; selecting a suitable machine learning/deep learning model; improving the accuracy of the applied model.
WisdomModel: convert data into wisdom
Authors: Mahmood Israa , Abdullah Hasanen 
Published: August 2021

PurposeTraditional classification algorithms always have an incorrect prediction. As the misclassification rate increases, the usefulness of the learning model decreases. This paper presents the development of a wisdom framework that reduces the error rate to less than 3% without human intervention.Design/methodology/approachThe proposed WisdomModel consists of four stages: build a classifier, isolate the misclassified instances, construct an automated knowledge base for the misclassified instances and rectify incorrect prediction. This approach will identify misclassified instances by comparing them against the knowledge base. If an instance is close to a rule in the knowledge base by a certain threshold, then this instance is considered misclassified.FindingsThe authors have evaluated the WisdomModel using different measures such as accuracy, recall, precision, f-measure, receiver operating characteristics (ROC) curve, area under the curve (AUC) and error rate with various data sets to prove its ability to generalize without human involvement. The results of the proposed model minimize the number of misclassified instances by at least 70% and increase the accuracy of the model minimally by 7%.Originality/valueThis research focuses on defining wisdom in practical applications. Despite of the development in information system, there is still no framework or algorithm that can be used to extract wisdom from data. This research will build a general wisdom framework that can be used in any domain to reach wisdom.
Surface roughness optimization in milling operation for aluminum alloy (Al 6061-T6) in aviation manufacturing elements
Authors: Seçgin Ömer , Sogut Mehmet Ziya 
Published: August 2021

Purpose
This paper aims that optimization parameters depending on machining processes examine to define for the milling process of AL 6061-T6 aluminum alloy used in the aviation industry.

Design/methodology/approach
The Taguchi method was used to study the optimal parameters. Furthermore, the effects of machining parameters on surface roughness were also evaluated by performing variance analysis. Optimum parameter levels were determined by Signal/Noise analysis.

Findings
It was determined that the parameter levels that optimize the surface roughness were “4000 rev/min for the rotational speed of the cutting tool, 0.4 mm for the cutting depth and the optimum value for the feedrate 500 mm/min.”

Research limitations/implications
It is limited by the precision of the manufacturing processes, the desired geometry and the exactness of the measurement make the machine productivity valuable in the production of parts.

Practical implications
By improving the optimal production parameters, reducing part production costs and waste amount in aviation has been seen as an important gain.

Social implications
Improving production methods and optimization parameters in production technologies will ensure the minimization of loss and waste. These developed parameters with optimizing the surface roughness will add value in this context.

Originality/value
It was determined that the parameter levels that optimize the surface roughness of aluminum considering manufacturing processes. Especially as process parameters, optimum feed rate has been developed for effective rotation speed and cutting depth for cutting tools.
Investigating the healthiness of food products on promotion: market brands and own brands
Authors: Beacom Emma , Hollywood Lynsey Elizabeth , McLaughlin Christopher , Furey Sinead , Price Ruth , McMahon-Beattie Una , Burns Amy 
Published: August 2021

PurposeThe purpose of this study is to investigate the proportionality of market brand (MB) foods versus supermarket own brand (OB) foods sold on promotion and to compare their healthiness.Design/methodology/approachAn existing dataset containing nutritional information about a variety of foods on promotion (n = 6,776) from 48 stores across 8 retail chains in Northern Ireland (NI) was reanalysed. Product healthiness was measured using a score aligned to the Food Standards Agency's Front of Pack nutrient labelling system. MBs and OBs were considered as a whole and in their respective subsets–international/national and regional MBs, and premium, mid-market and value tiered OBs.FindingsResults found a balance in favour of health (52.4% amber/green versus 47.6% red) across retailers' promotions in NI. Further, OB products were often found to be superior to MBs with regards to overall healthfulness, and regional brands were found to be less healthy than international/national brands.Research limitations/implicationsFindings rationale further retail research to compare nutritionally OB and MB product types, and further consumer research regarding important attributes of OBs.Practical implicationsRetailers should communicate the comparative healthiness of their OBs in comparison to MB alternatives, in addition to communicating comparative price savings. There is opportunity for retailers to increase visibility of mid-market and value OB tiers, and for regional MBs to improve the nutritional profile of products in line with the consumer trend for health.Originality/valueThis study provides a contribution by using data on OBs and MBs on promotion, and by investigating the nutritional differences between different tiers of OB and MB products.
Sustainability of operations through disruptive technologies in the petroleum supply chain
Authors: Kumar Sourabh , Barua Mukesh Kumar 
Published: August 2021

PurposeDisruptive technologies can significantly contribute to the sustainability of operations in the petroleum supply chain. The present study aims to identify the prime sustainable dimensions and disruptive technologies implementation in the supply chain of the petroleum industry. The authors used content analysis in the literature and experts input to explore the sustainable dimensions and disruptive technologies in the supply chain.Design/methodology/approachThis study used a hybrid method of hesitant fuzzy set and regret theory to identify the prominent sustainability dimensions and prominent disruptive technologies. This method emphasizes the decision-makers psychological characteristics under uncertain environments.FindingsThe result indicates that social responsibility, labor practices, safety and technical standards hold the most prominent sustainable dimensions in the petroleum supply chain. Further, the result also depicts that when consider an equal degree of regret and rejoice, artificial intelligence and big data could significantly enhance operations sustainability in the petroleum industry.Research limitations/implicationsThis study considers only 11 sustainable dimensions and 43 sustainable factors, whereas other dimensions and factors could also be considered in future research. The research uses hesitant fussy set and regret set theory to identify the prominent sustainable dimensions and disruptive technologies, whereas other multiple-criteria decision-making (MCDM) techniques can also be used.Originality/valueTo the best of the authors’ knowledge, this is the first paper to explore the sustainable dimensions (environmental, social and economic) and disruptive technologies in the supply chain of the petroleum industry. This research intended to guide the practitioners, policymakers and academicians to emphasize their effort toward sustainable operations supply chain management.
Development and validation of core technology competencies for systems librarian
Authors: Naveed Muhammad Asif , Siddique Nadeem , Mahmood Khalid 
Published: August 2021

Purpose
This study aimed to develop and validate a list of core technology competencies for systems librarian in Pakistan.

Design/methodology/approach
Survey method was used to conduct this investigation. A structured questionnaire, consisting of 52 competency statements categorized into six core technology areas, was developed based on an extensive literature review, experts’ scrutiny and pilot testing. The administration of the survey questionnaire was done though online environments such as related listservs and Facebook pages. The received 62 responses were imported into statistical package for social sciences and analyzed by computing means, standard deviations, Pearson correlation and t-test.

Findings
The results indicated six core technology areas where competencies of systems librarians needed to be developed, namely, basic computing, programming and Web publishing, computer networks, cloud computing, database management systems and information systems. The respondents validated 50 statements with an average mean score more than three. Only two statements received mean scores less than three. The results also indicated higher consistency of these statements as the value of Cronbach’s alpha was 0.973.

Research limitations/implications
This research attempted to identify and validate core technology competencies needed for systems librarians in Pakistan. It neither attempted to determine the weightage each competency should have if it was to be included in curriculum nor it intended to identify a detailed content for each core technology competency. In Pakistan, System librarians develop their knowledge and skills with the specialized computer subject by studying on their own, attending training workshops and on job experience. It is therefore worth mentioning here that the knowledge of the needed competencies may be limited.

Practical implications
Library and information science schools need to consider these competencies in developing and designing information curriculum with regard to management of library systems. This set of competencies help academicians in designing need-based curricula and training programs for existing and prospect system librarians in Pakistan.

Originality/value
This study would be a worthwhile contribution to the literature on competencies of information professionals especially systems librarians as no such study appeared providing pragmatic, evidenced and field-based insights toward proposed research area.
Entropy generation of natural heat exchange into a porous medium accumulated by a hybrid nanoliquid applying LTNE model
Authors: Shaker Hosein , Izadi Mohsen , Assareh Ehsanolah , Shehzad Sabir Ali , Sheremet Mikhail 
Published: August 2021

Purpose
This study aims to use the thermal non-equilibrium approach to inquire the entropy production and conjugate natural heat exchange in a porous medium. Entropy generation is studied separately for the solid matrix and the hybrid nanoliquid.

Design/methodology/approach
The characteristic equations are unraveled by applying the finite element method. Mathematical relations are used to calculate the generated entropy for the hybrid nanoliquid and matrix structure.

Findings
Based on the results, the produced entropy and the viscous friction term associated with the hybrid nanoliquid phase are not affected by increasing the thermal conductivity ratio of the rigid wall to nanoliquid. Moreover, a higher amount of entropy is generated by the thermal gradients in the hybrid nanoliquid phase compared to the solid matrix.

Originality/value
No investigation in the literature has been reported in this context.
How to manage and minimize food waste in the hotel industry: an exploratory research
Authors: Amicarelli Vera , Aluculesei Alina-Cerasela , Lagioia Giovanni , Pamfilie Rodica , Bux Christian 
Published: August 2021

Purpose
The hospitality industry is responsible for significant amounts of waste, more than one-third of which is food waste. Through the comparison between an Italian and a Romanian hotel, this paper aims to provide a better understanding of food waste management trends in the hotel industry as well as to highlight hotel kitchens and hotel food services weaknesses and opportunities to minimize food waste.

Design/methodology/approach
In-depth interviews, personal communication and observations were conducted to investigate food service planning, food procurement and food waste management, as well as to better comprehend current individuals’ understanding and attitudes, infrastructures, legislative culture and opportunities either from the managerial and the employees’ perspective. Data were analyzed according to a content analysis approach.

Findings
Three critical hot spots emerged from the analysis: prediction and check of guests’ attendance, communication and transparency with local suppliers and among departments within the unit and purchasing frequency and perishable food provisioning. The accurate forecasting of the number of guests and their nationality is fundamental in avoiding food waste at food service, as well as implementing transparency and communication with local suppliers.

Originality/value
Although academia and authorities have recognized the crucial importance of food waste management, food waste research in the hotel industry remains under-researched. The present exploratory research contributes to the scarce empirical studies about hotels’ food waste, giving theoretical and managerial recommendations for supporting further studies, highlighting the need for formal deals between hotels and local suppliers (food procurement), as well as the importance of food-networks that holds together companies, retailers and charities (food donation).
By-production of electricity and particulates: efficiency of Indian thermal power plants revisited
Authors: Sengupta Debarun , Mukherjee Deep 
Published: August 2021

Purpose
This paper studies the efficiency of Indian coal-fired thermal power plants (CTPPs) in by-production of electricity and particulates also known as Suspended Particulate Matter (SPM).

Design/methodology/approach
A non-radial directional distance function is optimized using data envelopment analysis to enumerate the overall inefficiency of CTPPs and its components in recent times. Further, second-stage regression analysis is conducted to identify factors that affect the inefficiency of plants.

Findings
The low inefficiency score for electricity generation suggests that most CTPPs operate close to the good output frontier. A high degree of emissions inefficiency is a challenge for Indian CTPPs. Ever-rising coal use inefficiency is a hindrance to control SPM emissions. The second stage regression analysis concludes that factors like ownership and capacity utilization play vital roles in determining a plant’s inefficiency level. Privately owned CTPPs have performed better in terms of technical inefficiency and emission inefficiency than plants owned by Central and State governments.

Originality/value
To the best of the authors’ knowledge, this study is one of the few published works that benchmark the productive and environmental performance of Indian CTPPs.
Good and bad high-frequency volatility spillovers among developed and emerging stock markets
Authors: Mensi Walid , Nekhili Ramzi , Vo Xuan Vinh , Kang Sang Hoon 
Published: August 2021

PurposeThis paper examines dynamic return spillovers and connectedness networks among international stock exchange markets. The authors account for asymmetry by distinguishing between positive and negative returns.Design/methodology/approachThis paper employs the spillover index of Diebold and Yilmaz (2012) to measure the volatility spillover index for total, positive and negative volatility.FindingsThe results show time-varying and asymmetric volatility spillovers among the stock markets under investigation. During the coronavirus disease 2019 (COVID-19) pandemic, bad volatility spillovers are more pronounced and dominated over good volatility spillovers, indicating contagion effects.Originality/valueThe presence of confirmed COVID-19 cases positively (negatively) affects the good and bad spillovers under low and intermediate (upper) quantiles. Both types of spillovers at various quantiles agree also influenced by the number of COVID-19 deaths.