The Digital Transformation of the Valuation Sector in the World of Algorithms

Over the years, the concept of digitalisation has rapidly integrated into many sectors. This Research Paper will discuss the valuation sector’s digital transformation, predominantly investigating the automated valuation models (AVMs) and their integration in valuation. Real estate is one of the oldest and the largest asset class in cities (Kok et al., 2017: 202). As explained by (Gilbertson and Preston,2005: 123), in mature economies, a large proportion of financial decision-making relates to property. Therefore, if the assets are not correctly valued then an extensive range of stakeholders are exposed. The 1970s property crash prompted RICS to publish the Red Book, setting out standards of valuation and professional conduct expected of valuers (Gilbertson and Preston, 2005: 124). However, the fluctuation and the relationship between value, worth and risk remain unchanged. The recent paradigm shift to the concept of digitalisation requires a discussion of economic development in relation to social development. This necessitates considering political (the role of governmental bodies concerning smart governance), social (individuals\dwellers in regards to raising the quality of life) and economic (such as real estate markets together with its stakeholders, including government, banks, building societies, insurance companies, and investment firms in regards to the coordination and collaboration) factors

Automated Valuation Models (AVMs): Machine Learning, namely Mass (Advanced) Valuation Methods and Algorithms

Digitalisation is becoming increasingly common within the valuation sector. Thus, it is vital to understand how traditional valuation methods are being replaced by machine learning technology, namely mass (advanced) valuation methods. According to Soni and Sadiq (2015: 100), real estate markets are popular with investors, who are keen to identify a fast way to play the market or to hedge against existing volatile portfolios. Therefore, an accurate prediction of house price is essential to prospective home owners, developers, investors, valuers, tax assessors, mortgage lenders and insurers. Demirci, O (2021) stated that the fluctuation and the relationship between value, worth, and risk remain unchanged in the current market. This means that the increased use of Automated Valuation Models (AVMs) requires a discussion of the machine learning technology, namely mass (advanced) valuation methods, which are the fundamental basis of the algorithms used within the valuation sector. As defined by Erdem (2017), valuation can be categorised into traditional, statistical and modern methods. This Research Paper will investigate both the statistical and modern methods of valuation and their application to the real estate valuation. In particular, it will look at the main limitations of the traditional valuation methods in respect to their accuracy, consistency and speed (Jahanshiri, 2011; Wang & Wolverton, 2012; Adetiloye & Eke, 2014). Moreover, these methods will be compared against mass (advanced) valuation methods, when there is a need to value a group of properties. Indeed, with the increasing volume of transactions and changing marketplace of real estate, mass (advanced) valuation has been widely adopted in many countries for different purposes, including assessment of property tax (Osborn, 2014). https://doi.org/10.13140/RG.2.2.12649.4208

Advances in plasmonic technologies for point of care applications

Infectious diseases have considerable economic and societal impact on developing settings. For instance, malaria is observed more commonly in sub-Saharan Africa and India. The societal impact of acquired immune deficiency syndrome (AIDS) and tuberculosis is high, through targeting adults in villages and leaving behind declining populations. Highly sensitive and specific lab assays such as cell culture methods, polymerase chain reaction (PCR), and enzyme-linked immunosorbent assay (ELISA) are available for diagnosis of infectious diseases in the developed world. They require sample transportation, manual preparation steps, and skilled and well-trained technicians. These clinical conventional methods provide results in several hours to days, precluding rapid detection and response at the primary care settings. Another diagnostic challenge is identifying multiple pathogens

Volumetric evaluation of temporal bone structures in the cases with bilateral tinnitus: clinical and morphometrical study

Background: Tinnitus is the recognition of sound in the absence of any external auditory stimulus to the noise of ringing in the ears. Middle ear aeration carries important role for ossicular coupling and normal hearing. There is restricted morphometric data on the cases with bilateral tinnitus. Materials and methods: In this study we evaluated hearing findings of 18 cases with subjective nonpulsatile bilateral tinnitus and also morphometry and volumetry of temporal bone substructures on the computed tomography images using stereological method compared with the gender and age matched 12 healthy subjects. Duration of tinnitus, exposing acoustic trauma or/and high level noise levels, evaluation of middle ear volume, jugular bulb levels, distances between jugular bulb and both oval window and middle ear were evaluated. Results: Both males and females with tinnitus showed worse hearing thresholds through bone and air conductions than healthy subjects but it was not statistically significant. Pure tone thresholds through bone and air conductions were not statistically different in both sexes with bilateral tinnitus. Right middle ear volume of the cases with bilateral tinnitus was mean 5.57 cm3 for males and 5.64 cm3 for females; and also the left middle ear volume of the cases with bilateral tinnitus was mean 5.87 cm3 for males and 5.65 cm3 for females. There were no significant differences between the cases with bilateral tinnitus and the control subjects according to the side of the body. < strong > Conclusions: The data on the hearing findings and morphometrical evaluation of the cases with bilateral tinnitus may be important for anatomists and clinicians. (Folia Morphol 2018; 77, 1: 57–64)

Enhancing acetic acid and 5-hydroxymethyl furfural tolerance of C. saccharoperbutylacetonicum through adaptive laboratory evolution

Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.procbio.2020.11.013.In this study, adaptive laboratory evolution (ALE) was applied to isolate four strains of Clostridium saccharoperbutylacetonicum able to grow in the presence of hemicellulosic hydrolysate inhibitors unsupported by the parental strain. Among them, isolate RAC-25 presented the best fermentative performance, producing 22.1g/L of ABE and 16.7g/L of butanol. Genome sequencing revealed a deletion in the arabinose transcriptional repressor gene (araR) and a mutation in the anti-sigma factor I that promoted a downregulation of sigI. Gene expression analysis indicated high expression of genes related to H+-pumps (ATP synthases), proline biosynthesis (gamma phosphate reductase) and chaperonins (Grol), suggesting an integrated mechanism that is probably coordinated by the repression of sigI. Therefore, in addition to highlighting the power of ALE for selecting robust strains, our results suggest that sigI and araR may be interesting gene targets for increased tolerance toward inhibitor compounds relevant for lignocellulosic biofuels production.The authors would like to thank the Brazilian Center for Research in Energy and Materials (CNPEM) for providing access to the bioprocess facility of the Brazilian Biorenewables National Laboratory, and CNPq (400803/2013-5), FCT (UID/BIO/04469), BioTecNorte Operation (NORTE-01-0145-FEDER-000004) and Portuguese Biological Data Network” (ref. LISBOA-01-0145-FEDER-022231) for financial support.info:eu-repo/semantics/publishedVersio

Effect of antenatal milk expression education on lactation outcomes in birthing people with pre-pregnancy body mass index ≥ 25: Protocol for a randomized, controlled trial

Background: Birthing people with pre-pregnancy body mass indices (BMIs) ≥ 25 kg/m2, particularly those without prior breastfeeding experience, are at increased risk for suboptimal lactation outcomes. Antenatal milk expression (AME) may be one way to counteract the negative effects of early infant formula supplementation common in this population. Methods: This ongoing, randomized controlled trial in the United States evaluates the efficacy of a telelactation-delivered AME education intervention versus an attention control condition on lactation outcomes to 1 year postpartum among 280 nulliparous-to-primiparous, non-diabetic birthing people with pre-pregnancy BMI ≥ 25 kg/m2. The assigned study treatment is delivered via four weekly online video consultations between gestational weeks 37-40. Participants assigned to AME meet with study personnel and a lactation consultant to learn and practice AME. Instructions are provided for home practice of AME between study visits. Control group participants view videos on infant care/development at study visits. Participants complete emailed surveys at enrollment (340/7-366/7 gestational weeks) and 2 weeks, 6 weeks, 12 weeks, 6 months, and 12 months postpartum. Surveys assess lactation and infant feeding practices; breastfeeding self-efficacy, attitudes, and satisfaction; perception of insufficient milk; onset of lactogenesis-II; lactation support and problems; and reasons for breastfeeding cessation. Surveys also assess factors associated with lactation outcomes, including demographic characteristics, health problems, birth trauma, racial discrimination, and weight stigma. Health information and infant feeding data are abstracted from the pregnancy and birth center electronic health record. Milk samples are collected from the intervention group at each study visit and from both groups at each postpartum follow-up for future analyses. Qualitative interviews are conducted at 6 weeks postpartum to understand AME experiences. Primary outcomes of interest are breastfeeding exclusivity and breastfeeding self-efficacy scores at 2 weeks postpartum. Outcomes will be examined longitudinally with generalized linear mixed-effects modeling. Discussion: This is the first adequately powered trial evaluating the effectiveness of AME among U.S. birthing people and within a non-diabetic population with pre-pregnancy BMI ≥ 25 kg/m2. This study will also provide the first evidence of acceptability and effectiveness of telelactation-delivered AME. Trial registration: ClinicalTrials.gov: NCT04258709