• Automated prediction of examinee proficiency from short-answer questions

      Ha, Le; Yaneva, Victoria; Harik, Polina; Pandian, Ravi; Morales, Amy; Clauser, Brian (International Committee on Computational Linguistics, 2020-12-10)
      This paper brings together approaches from the fields of NLP and psychometric measurement to address the problem of predicting examinee proficiency from responses to short-answer questions (SAQs). While previous approaches train on manually labeled data to predict the human ratings assigned to SAQ responses, the approach presented here models examinee proficiency directly and does not require manually labeled data to train on. We use data from a large medical exam where experimental SAQ items are embedded alongside 106 scored multiple-choice questions (MCQs). First, the latent trait of examinee proficiency is measured using the scored MCQs and then a model is trained on the experimental SAQ responses as input, aiming to predict proficiency as its target variable. The predicted value is then used as a “score” for the SAQ response and evaluated in terms of its contribution to the precision of proficiency estimation.
    • An automatic method to identify citations to journals in news stories: A case study of UK newspapers citing Web of Science journals

      Kousha, Kayvan; Thelwall, Mike (The Chinese Academy of Sciences, 2019-08-30)
      Purpose: Communicating scientific results to the public is essential to inspire future researchers and ensure that discoveries are exploited. News stories about research are a key communication pathway for this and have been manually monitored to assess the extent of press coverage of scholarship. Design / methodology /Approach: To make larger scale studies practical, this paper introduces an automatic method to extract citations from newspaper stories to large sets of academic journals. Curated ProQuest queries were used to search for citations to 9,639 Science and 3,412 Social Science Web of Science (WoS) journals from eight UK daily newspapers during 2006-2015. False matches were automatically filtered out by a new program, with 94% of the remaining stories meaningfully citing research. Findings: Most Science (95%) and Social Science (94%) journals were never cited by these newspapers. Half of the cited Science journals covered medical or health-related topics, whereas 43% of the Social Sciences journals were related to psychiatry or psychology. From the citing news stories, 60% described research extensively and 53% used multiple sources, but few commented on research quality. Research Limitations: The method has only been tested in English and from the ProQuest Newspapers database. Practical implications: Others can use the new method to systematically harvest press coverage of research. Originality /value: An automatic method was introduced and tested to extract citations from newspaper stories to large sets of academic journals.
    • Automatically detecting open academic review praise and criticism

      Thelwall, Michael; Papas, Eleanor-Rose; Nyakoojo, Zena; Allen, Liz; Weigert, Verena (Emerald, 2020-06-15)
      Purpose: Peer reviewer evaluations of academic papers are known to be variable in content and overall judgements but are important academic publishing safeguards. This article introduces a sentiment analysis program, PeerJudge, to detect praise and criticism in peer evaluations. It is designed to support editorial management decisions and reviewers in the scholarly publishing process and for grant funding decision workflows. The initial version of PeerJudge is tailored for reviews from F1000Research’s open peer review publishing platform. Design/methodology/approach: PeerJudge uses a lexical sentiment analysis approach with a human-coded initial sentiment lexicon and machine learning adjustments and additions. It was built with an F1000Research development corpus and evaluated on a different F1000Research test corpus using reviewer ratings. Findings: PeerJudge can predict F1000Research judgements from negative evaluations in reviewers’ comments more accurately than baseline approaches, although not from positive reviewer comments, which seem to be largely unrelated to reviewer decisions. Within the F1000Research mode of post-publication peer review, the absence of any detected negative comments is a reliable indicator that an article will be ‘approved’, but the presence of moderately negative comments could lead to either an approved or approved with reservations decision. Originality/value: PeerJudge is the first transparent AI approach to peer review sentiment detection. It may be used to identify anomalous reviews with text potentially not matching judgements for individual checks or systematic bias assessments.
    • Awareness of big data concept in the Dominican Republic construction industry: an empirical study

      Reyes-Veras, Paola; Renukappa, Suresh; Suresh, Subashini (Teesside University, 2020-10-01)
      The construction industry, being one of the main characters in the ever-demanding need for technology developments, sometimes falls short of other industries in terms of implementation. The adoption of Big Data (BD) in industries like health and retail has had positive impacts in aspects such as decision-making processes and forecasting trends that allow planning some future business movements in advance. Hence, the question of whether these results can be recreated in construction industry. Therefore, this paper addresses the level of awareness identified as the first step towards implementation of the BD Concept within the construction industry of Dominican Republic (DR). Since little to no information exist on the subject the selected approach to perform this research was qualitative, twenty-one semi-structured interviews were studied using content analysis. Four levels of awareness is developed based on the Endsley situation awareness model. The results showed that nearly ninety-five percent of the interviewees had either no knowledge or a very basic awareness of the BD requirements or intermediate awareness but only five percent had actually applied BD in the construction industry. This paper provides the level of awareness of BD in the DR construction industry and provides evidence for the need to provide continuous professional development programmes for construction professionals and a need for an update of curriculum in construction-related education.
    • Awareness of big data concept in the Dominican Republic construction industry: an empirical study

      Renukappa, Suresh; Suresh, Subashini; Reyes-Veras, Paola (Emerald, 2021-09-24)
      Purpose –The construction industry, being one of the main activities in the ever-demanding need for technology developments, sometimes falls short of other industries in terms of implementation. The adoption of Big Data (BD) in industries like health and retail has had positive impacts in aspects such as decision-making processes and forecasting trends that allows planning some future business movements. Hence, the question of whether these results can be recreated in the construction industry. Therefore, this paper addresses the level of awareness identified as a first step towards implementation of the BD concept within the construction industry in the Dominican Republic (DR). Design/methodology/approach – Since little to no information exist on the subject, the selected approach to perform this research was qualitative methodology, twenty-one semi-structured interviews were studied using situational awareness. Four levels of awareness were developed based on the Endsley situation awareness model. Findings – The results showed that nearly ninety-five per cent of the interviewees had either no knowledge or very basic awareness of the BD requirements or intermediate awareness but only five per cent had applied BD concepts in the construction industry. Originality/value -This paper provides an exploration of the level of awareness of BD in the DR construction industry and delivers evidence for the need to provide continuous professional development programmes for construction professionals and a need for an update of the curriculum in construction-related education.
    • Bacillus subtilis natto: A non-toxic source of poly-γ-glutamic acid that could be used as a cryoprotectant for probiotic bacteria

      Bhat, AR; Irorere, VU; Bartlett, T; Hill, D; Kedia, G; Morris, MR; Charalampopoulos, D; Radecka, I; University of Wolverhampton, Wolverhampton, UK. i.radecka@wlv.ac.uk. (Springer Science and Business Media LLC, 2013-07-05)
      It is common practice to freeze dry probiotic bacteria to improve their shelf life. However, the freeze drying process itself can be detrimental to their viability. The viability of probiotics could be maintained if they are administered within a microbially produced biodegradable polymer - poly-γ-glutamic acid (γ-PGA) - matrix. Although the antifreeze activity of γ-PGA is well known, it has not been used for maintaining the viability of probiotic bacteria during freeze drying. The aim of this study was to test the effect of γ-PGA (produced by B. subtilis natto ATCC 15245) on the viability of probiotic bacteria during freeze drying and to test the toxigenic potential of B. subtilis natto. 10% γ-PGA was found to protect Lactobacillus paracasei significantly better than 10% sucrose, whereas it showed comparable cryoprotectant activity to sucrose when it was used to protect Bifidobacterium breve and Bifidobacterium longum. Although γ-PGA is known to be non-toxic, it is crucial to ascertain the toxigenic potential of its source, B. subtilis natto. Presence of six genes that are known to encode for toxins were investigated: three component hemolysin (hbl D/A), three component non-haemolytic enterotoxin (nheB), B. cereus enterotoxin T (bceT), enterotoxin FM (entFM), sphingomyelinase (sph) and phosphatidylcholine-specific phospholipase (piplc). From our investigations, none of these six genes were present in B. subtilis natto. Moreover, haemolytic and lecithinase activities were found to be absent. Our work contributes a biodegradable polymer from a non-toxic source for the cryoprotection of probiotic bacteria, thus improving their survival during the manufacturing process. © 2013 Bel-Rhlid et al.
    • Bacterial Cell-Mineral Interface, Its Impacts on Biofilm Formation and Bioremediation

      Pouran, Hamid; Hussain, Chaudhery (Springer, 2019-03-29)
      This chapter aims to provide a better understanding of the bacterial cell attachment and biofilm formation on the mineral surfaces, which would result in improving our knowledge about: the interfacial forces governing the bacterial cell attachment, predicting trends of the biofilm formation and consequently biodegradation rates, and the contaminant’s fate in the diverse geological media (Pouran HM. Studying molecular and nanoscale interactions at metal oxide surfaces and their effects on bacterial adhesion, 2009). In both aqueous and terrestrial environments, bacterial cells tend to be attached to a surface and form biofilm. If they are associated to, e.g., a mineral surface, bacterial cells would remain in a more stable microenvironment instead of being removed by the water shear stress. Even the bacterial planktonic phase can be considered as a mechanism for translocation from one surface to the other rather than a prime lifestyle (Watnick and Kolter 2000; Young 2006). The biofilm formation, which completely covers the surface, initially begins by the adhesion of a small quantity of cells (Vadillo-rodri et al. 2006; Pouran et al. 2017). Among the different indigenous microbial species in the contaminated environments, some are capable of degrading pollutants and participating in the environmental remediation process. The bioremediation process of the contaminated soils and waters is often considered a promising low risk management tool. Even when the contamination poses an imminent threat and other approaches are essential, bioremediation often is a viable secondary strategy for the site maintenance (Haws et al. 2006; Pouran et al. 2017). Natural environments are dynamic and complex systems; therefore, characterization and identifying the underlying processes governing the contaminant’s fate are not easy. Examples of the natural environments heterogeneity are the diverse physicochemical properties of the soils and aquifers matrices (Stumm and Morgan 1996). As the soils and sediments are the prime surfaces for the bacterial cell attachment in most natural environments, elucidation of the surface properties of these constituents and their role in initiating cell adhesion and biofilm formation are of the key importance in understanding the bioremediation process. In fact, the cell-mineral interface reactions not only influence the biodegradation process but many natural phenomena are affected by them. Understanding role of physicochemical interactions at the bacterial cells and minerals interface in the cell adhesion (as well as biofilm formation, development, and behavior) is essential for planning effective bioremediation techniques. It could potentially help us to predict the contaminants’ fate, and trends of the biodegradation rates in different environments. Consequently, the improved knowledge of the cell-mineral interface enable us to design and apply more sophisticated bioremediation techniques as a viable approach towards tackling the soil and water environmental pollution problems. Figure 1 schematically represents an aquifer and biofilm formation on some of the most abundant minerals in the environment, iron and aluminum oxides. It also indicates some the major effects of cell-mineral interface interactions on different environmental processes (Stumm and Morgan 1996; Zachara and Fredrickson 2004; Cornell and Schwertmann 2003).
    • Bacterial synthesis of biodegradable polyhydroxyalkanoates.

      Verlinden, Rob A. J.; Hill, David J.; Kenward, M.A.; Williams, Craig D.; Radecka, Izabela (Wiley InterScience, 2007)
      Various bacterial species accumulate intracellular polyhydroxyalkanoates (PHAs) granules as energy and carbon reserves inside their cells. PHAs are biodegradable, environmentally friendly and biocompatible thermoplastics. Varying in toughness and flexibility, depending on their formulation, they can be used in various ways similar to many nonbiodegradable petrochemical plastics currently in use. They can be used either in pure form or as additives to oil-derived plastics such as polyethylene. However, these bioplastics are currently far more expensive than petrochemically based plastics and are therefore used mostly in applications that conventional plastics cannot perform, such as medical applications. PHAs are immunologically inert and are only slowly degraded in human tissue, which means they can be used as devices inside the body. Recent research has focused on the use of alternative substrates, novel extraction methods, genetically enhanced species and mixed cultures with a view to make PHAs more commercially attractive.
    • Bacterial-derived Polymer Poly-y-Glutamic Acid (y-PGA)-based micro/nanoparticles as a delivery system for antimicrobials and other biomedical applications

      Khalil, Ibrahim; Burns, Alan; Radecka, Iza; Kowalczuk, Marek; Khalaf, Tamara; Adamus, Grazyna; Johnston, Brian; Khechara, Martin (2017-02-02)
      Abstract: In the past decade, poly-γ-glutamic acid (γ-PGA)-based micro/nanoparticles have garnered remarkable attention as antimicrobial agents and for drug delivery, owing to their controlled and sustained-release properties, low toxicity, as well as biocompatibility with tissue and cells. γ-PGA is a naturally occurring biopolymer produced by several gram-positive bacteria that, due to its biodegradable, non-toxic and non-immunogenic properties, has been used successfully in the medical, food and wastewater industries. Moreover, its carboxylic group on the side chains can offer an attachment point to conjugate antimicrobial and various therapeutic agents, or to chemically modify the solubility of the biopolymer. The unique characteristics of γ-PGA have a promising future for medical and pharmaceutical applications. In the present review, the structure, properties and micro/nanoparticle preparation methods of γ-PGA and its derivatives are covered. Also, we have highlighted the impact of micro/nanoencapsulation or immobilisation of antimicrobial agents and various disease-related drugs on biodegradable γ-PGA micro/nanoparticles.
    • Baricitinib in rheumatoid arthritis – real world cross-sectional study

      Sagdeo, Amol; Askari, Ayman; Morrissey, Hana; Ball, Patrick (Bentham Open, 2020-11-25)
      Introduction: Rheumatoid arthritis (RA) is the most common cause of inflammatory polyarthritis. In RA, increased circulating levels of pro-inflammatory cytokines contribute to the overall symptomatology of fatigue, pain, and joint stiffness. Baricitinib is an orally administered biologic DMARD, used in RA patients, inhibiting signaling via JAK1/JAK2 inhibition, reducing the release of pro-inflammatory cytokines. Objective: To explore the efficacy and tolerability for baricitinib in a local population. Methods: A cross-sectional study was carried out to review data of RA patients on Baricitinib from the researchers’ own clinic, since its approval in August 2017. The data was collected from an anonymized electronic patient records report. The clinical response was then classified into mild, moderate, and significant improvement. Results and Discussion: Overall, 27 out of 37 patients (72.9%) showed clinical improvement with baricitinib. In 9(24.3%) out of 37 patients, the dose had to be reduced to either 2mg/day or 2mg/day - 4mg/day on alternate days. In four of the 9 patients’ where the dose was reduced due to infections (UTI or sinuses), they subsequently experienced fewer infections while maintaining moderate improvement in their RA. Conclusion: There is a need for longer-term and larger studies to evaluate the full side effects profile of baricitinib in the local population.
    • Barriers for Implementing solar energy initiatives in Nigeria: an empirical study

      Renukappa, Suresh; Suresh, Subashini; Abdullahi, Dahiru; Oloke, David (Emerald, 2021-01-26)
      Purpose Despite the abundant renewable energy potential in the Nigeria, power sector stakeholders have not paid attention to the prospect of natural resources that can be utilised when it is properly harnessed. Although, a very negligible fraction of the population has invested in solar photovoltaic (PVs) for home solution, the initiative was only made public commercialised under the public private partnership (PPP) and the objectives of the Power Sector Reform Act. 2005. It is, therefore, aimed to investigate the causes and insight of the barriers that are responsible for the slow implementation of the solar energy initiative in Nigeria. Design/methodology/approach An empirical study was performed in Nigeria. The study was conducted qualitatively, through semi-structured face-to face interviews of 25 participants. The interviews were recorded, transcribed, interpreted, coded, categorised into themes, and analysed by content analysis. Findings The study reveals technological, financial, political, and social barriers have been the reason for slowing down solar energy development in Nigeria. While the technical barrier is a challenge to the solar energy implementation, socio-cultural issues have also been an obstacle to the implementation process. It is suggested that the stakeholders of the initiatives, to proffer sustainable policies to enable public and private promoters to be able to generate, and distribute electricity through solar PV, to complement the inadequate conventional electricity sources from the grids. Originality/value The paper provides a richer insight into the understanding and awareness of barriers for implementing solar energy strategies in Nigeria.
    • Barriers to early detection of cognitive impairment in the elderly despite the availability of simple cognitive screening tools and the pharmacist’s role in early detection and referral

      Abed, H; Ball, Patrick; Morrissey, Hana (Society of Hospital Pharmacists of Australia available via Wiley Online Library, 2017-07-05)
      Aim The aim of this review is to identify a suitable cognitive screening tool that can be used by the pharmacist during home medication review in addition to calculating the medications’ total anticholinergic burden (ACB). Data sources A search of the literature was conducted using PubMed, Embase, Medline and Google Scholar databases to identify relevant studies using the following keywords: ‘cognitive impairment’, ‘cognitive impairment AND diagnosis’, ‘cognitive scales’, ‘dementia’, ‘delirium’, ‘pharmacist role’, ‘mini-mental state examination (MMSE)’, ‘the Rowland dementia assessment scale (RUDAS)’, ‘the Alzheimer's Disease Assessment Scale - Cognition (ADAS-Cog)’ and ‘barriers and problems’. Only informational websites, clinical trials and review articles were included. Results The MMSE, RUDAS, ADAS-Cog, Psychogeriatric Assessment Scale (PAS) and Kimberley Indigenous Cognitive Assessment (KICA-Cog) require specialist training. The anxiety and depression checklist (K10) and ‘worried about your memory’ (WAYM) can be self-administered without prior training. The ACB scoring system can also be used to determine the total medications ACB. Conclusion The K10 and WAYM can be used by the pharmacist during medication reviews to detect cognitive impairment early and refer the elderly for further medical care supported by the calculated score for the patient‘s total medications‘ ACB.
    • Barriers to MNEs green business models in the UK construction sector: An ISM analysis

      Abuzeinab, Amal; Arif, Mohammed; Qadri, Mohammad Asim (Elsevier, 2017-01-11)
      The environmental and economic benefits of green business models (GBMs) are considerable if current barriers can be identified and ways of overcoming them developed. In this study, barriers to GBMs are identified by conducting a qualitative study. Nineteen semi-structured interviews were conducted with selected UK construction sector experts from academia and industry and the results were obtained by applying thematic analysis. Five major categories of barriers emerged: government constraints; financial constraints; sector constraints; company constraints; and lack of demand. To understand the collective impact of these barriers, the interpretive structural modelling (ISM) method was used. The ISM-based model showed that government constraints are driving the rest of the barriers followed by financial and construction sector constraints equally then the by company constraints. Surprisingly, lack of demand appeared to have the least significance in hindering GBM transformation compared to the rest of the barriers. The results present a clear picture of the green construction market relevant to multinational enterprises (MNEs) intending to enter the UK. MNEs are therefore influenced by the government on strategic planning and capability building for GBMs. Effective engagement with the government will generate institutional advantages resulting in legitimacy and trust for MNEs in the UK markets.
    • Baseline and triangulation geometry in a standard plenoptic camera

      Hahne, Christopher; Aggoun, Amar; Velisavljevic, Vladan; Fiebig, Susanne; Pesch, Matthias (Springer, 2017-08-20)
      In this paper, we demonstrate light field triangulation to determine depth distances and baselines in a plenoptic camera. Advances in micro lenses and image sensors have enabled plenoptic cameras to capture a scene from different viewpoints with sufficient spatial resolution. While object distances can be inferred from disparities in a stereo viewpoint pair using triangulation, this concept remains ambiguous when applied in the case of plenoptic cameras. We present a geometrical light field model allowing the triangulation to be applied to a plenoptic camera in order to predict object distances or specify baselines as desired. It is shown that distance estimates from our novel method match those of real objects placed in front of the camera. Additional benchmark tests with an optical design software further validate the model’s accuracy with deviations of less than ±0.33% for several main lens types and focus settings. A variety of applications in the automotive and robotics field can benefit from this estimation model.
    • Basic knowledge on leprosy: a short review

      Lowe, Chamodika (SciRes Literature LLC, 2021-05-21)
      Leprosy is a chronic disease which is caused by the infection of Mycobacterium leprae bacterium and leads to neurological consequences. Regardless of its slow progressiveness, it is an exceptionally serious disease that is continuing to be a challenging health problem around the world. Early diagnosis and treatment is much important in controlling Leprosy. Already published articles and books on Leprosy have been studied and summarized in this review to present a basic understanding on pathogenesis, symptoms, diagnosis and treatment of Leprosy.
    • Basic model of purposeful kinesis

      Gorban, Alexander N.; Çabukoǧlu, Nurdan (Elsevier, 2018-02-05)
      The notions of taxis and kinesis are introduced and used to describe two types of behaviour of an organism in non-uniform conditions: (i) Taxis means the guided movement to more favourable conditions; (ii) Kinesis is the non-directional change in space motion in response to the change of conditions. Migration and dispersal of animals has evolved under control of natural selection. In a simple formalisation, the strategy of dispersal should increase Darwinian fitness. We introduce new models of purposeful kinesis with diffusion coefficient dependent on fitness. The local and instant evaluation of Darwinian fitness is used, the reproduction coefficient. New models include one additional parameter, intensity of kinesis, and may be considered as the minimal models of purposeful kinesis. The properties of models are explored by a series of numerical experiments. It is demonstrated how kinesis could be beneficial for assimilation of patches of food or of periodic fluctuations. Kinesis based on local and instant estimations of fitness is not always beneficial: for species with the Allee effect it can delay invasion and spreading. It is proven that kinesis cannot modify stability of homogeneous positive steady states.
    • Bat algorithm–based beamforming for mmWave massive MIMO systems

      Shahjehan, W; Riaz, A; Khan, I; Sadiq, AS; Khan, S; Khan, MK (Wiley, 2019-09-10)
      © 2019 John Wiley & Sons, Ltd. In this paper, an optimized analog beamforming scheme for millimeter-wave (mmWave) massive MIMO system is presented. This scheme aims to achieve the near-optimal performance.by searching for the optimized combination of analog precoder and combiner. In order to compensate for the occurrence of attenuation in the magnitude of mmWave signals, the codebook-dependent analog beamforming in conjunction with precoding at transmitting end and combining signals at the receiving end is utilized. Nonetheless, the existing and traditional beamforming schemes involve a more difficult and complicated search for the optimal combination of analog precoder/combiner matrices from predefined codebooks. To solve this problem, we have referred to a modified bat algorithm to find the optimal combination value. This algorithm will explore the possible pairs of analog precoder/combiner as a way to come up with the best match in order to attain near-optimal performance. The analysis shows that the optimized beamforming scheme presented in this paper can improve the performance that is very close to the beam steering benchmark that we have considered.
    • A Bayesian hurdle quantile regression model for citation analysis with mass points at lower values

      Shahmandi, Marzieh; Wilson, Paul; Thelwall, Michael (MIT Press, 2021-07-21)
      Quantile regression is a technique to analyse the effects of a set of independent variables on the entire distribution of a continuous response variable. Quantile regression presents a complete picture of the effects on the location, scale, and shape of the dependent variable at all points, not just at the mean. This research focuses on two challenges for the analysis of citation counts by quantile regression: discontinuity and substantial mass points at lower counts, such as zero, one, two, and three. A Bayesian two-part hurdle quantile regression model was proposed by King and Song (2019) as a suitable candidate for modeling count data with a substantial mass point at zero. Their model allows the zeros and non-zeros to be modeled independently but simultaneously. It uses quantile regression for modeling the nonzero data and logistic regression for modeling the probability of zeros versus nonzeros. Nevertheless, the current paper shows that substantial mass points also at one, two, and three for citation counts will nearly certainly affect the estimation of parameters in the quantile regression part of the model in a similar manner to the mass point at zero. We update the King and Song model by shifting the hurdle point from zero to three, past the main mass points. The new model delivers more accurate quantile regression for moderately to highly cited articles, especially at quantiles corresponding to values just beyond the mass points, and enables estimates of the extent to which factors influence the chances that an article will be low cited. To illustrate the advantage and potential of this method, it is applied separately to both simulated citation counts and also seven Scopus fields with collaboration, title length, and journal internationality as independent variables.
    • BDI for Intelligent Agents in Computer Games

      Davies, N.P.; Mehdi, Qasim (The University of Wolverhampton, School of Computing and Information Technology, 2006)
      With the emergence of complex computer games and advanced gaming hardware, possibilities for overcoming some of the deficiencies in traditional game AI are becoming feasible. These deficiencies include repetitive, predictable, and inhuman behaviour are caused by the reliance on simple reactive AI techniques. By using more sophisticated AI and agent techniques, we intend to overcome some of these problem areas. The aim of our research is to create new forms of intelligent characters (agents) that will exhibit human-like intelligence and provide more challenging and entertaining virtual opponents and team mates for computer games. We present here our prototype application that implements a BDI agent system within the 3D computer game Unreal Tournament via GameBots and JavaBots technology.
    • Beating bias: Facing gender equality in the built environment sector through the support of technology

      Chinyio, Ezekiel (Athens Institute for Education and Research, 2019-06-24)