15,261 research outputs found
Heterogeneity in mode choice behavior: A spatial latent class approach based on accessibility measures
We propose a method to estimate mode choice models, where preference parameters are sensitive to the spatial context of the trip origin, challenging traditional assumptions of spatial homogeneity in the relationship between travel modes and the built environment. The framework, called Spatial Latent Classes (SLC), is based on the integrated choice and latent class approach, although instead of defining classes for the decision maker, it estimates the probability of a location belonging to a class, as a function of spatial attributes. For each Spatial Latent Class, a different mode choice model is specified, and the resulting behavioral model for each location is a weighted average of all class-specific models, which is estimated to maximize the likelihood of reproducing observed travel behavior. We test our models with data from Portland, Oregon, specifying spatial class membership models as a function of local and regional accessibility measures. Results show the SLC increases model fit when compared with traditional methods and, more importantly, allows segmenting urban space into meaningful zones, where predominant travel behavior patterns can be easily identified. We believe this is a very intuitive way to spatially analyze travel behavior trends, allowing policymakers to identify target areas of the city and the accessibility levels required to attain desired modal splits
Pretrained Embeddings for E-commerce Machine Learning: When it Fails and Why?
The use of pretrained embeddings has become widespread in modern e-commerce
machine learning (ML) systems. In practice, however, we have encountered
several key issues when using pretrained embedding in a real-world production
system, many of which cannot be fully explained by current knowledge.
Unfortunately, we find that there is a lack of a thorough understanding of how
pre-trained embeddings work, especially their intrinsic properties and
interactions with downstream tasks. Consequently, it becomes challenging to
make interactive and scalable decisions regarding the use of pre-trained
embeddings in practice.
Our investigation leads to two significant discoveries about using pretrained
embeddings in e-commerce applications. Firstly, we find that the design of the
pretraining and downstream models, particularly how they encode and decode
information via embedding vectors, can have a profound impact. Secondly, we
establish a principled perspective of pre-trained embeddings via the lens of
kernel analysis, which can be used to evaluate their predictability,
interactively and scalably. These findings help to address the practical
challenges we faced and offer valuable guidance for successful adoption of
pretrained embeddings in real-world production. Our conclusions are backed by
solid theoretical reasoning, benchmark experiments, as well as online testings
Genomic prediction in plants: opportunities for ensemble machine learning based approaches [version 2; peer review: 1 approved, 2 approved with reservations]
Background: Many studies have demonstrated the utility of machine learning (ML) methods for genomic prediction (GP) of various plant traits, but a clear rationale for choosing ML over conventionally used, often simpler parametric methods, is still lacking. Predictive performance of GP models might depend on a plethora of factors including sample size, number of markers, population structure and genetic architecture. Methods: Here, we investigate which problem and dataset characteristics are related to good performance of ML methods for genomic prediction. We compare the predictive performance of two frequently used ensemble ML methods (Random Forest and Extreme Gradient Boosting) with parametric methods including genomic best linear unbiased prediction (GBLUP), reproducing kernel Hilbert space regression (RKHS), BayesA and BayesB. To explore problem characteristics, we use simulated and real plant traits under different genetic complexity levels determined by the number of Quantitative Trait Loci (QTLs), heritability (h2 and h2e), population structure and linkage disequilibrium between causal nucleotides and other SNPs. Results: Decision tree based ensemble ML methods are a better choice for nonlinear phenotypes and are comparable to Bayesian methods for linear phenotypes in the case of large effect Quantitative Trait Nucleotides (QTNs). Furthermore, we find that ML methods are susceptible to confounding due to population structure but less sensitive to low linkage disequilibrium than linear parametric methods. Conclusions: Overall, this provides insights into the role of ML in GP as well as guidelines for practitioners
Norsk rå kumelk, en kilde til zoonotiske patogener?
The worldwide emerging trend of eating “natural” foods, that has not been
processed, also applies for beverages. According to Norwegian legislation, all
milk must be pasteurized before commercial sale but drinking milk that has
not been heat-treated, is gaining increasing popularity. Scientist are warning
against this trend and highlights the risk of contracting disease from milkborne
microorganisms. To examine potential risks associated with drinking
unpasteurized milk in Norway, milk- and environmental samples were
collected from dairy farms located in south-east of Norway. The samples
were analyzed for the presence of specific zoonotic pathogens; Listeria
monocytogenes, Campylobacter spp., and Shiga toxin-producing Escherichia
coli (STEC). Cattle are known to be healthy carriers of these pathogens, and
Campylobacter spp. and STEC have a low infectious dose, meaning that
infection can be established by ingesting a low number of bacterial cells. L.
monocytogenes causes one of the most severe foodborne zoonotic diseases,
listeriosis, that has a high fatality rate. All three pathogens have caused milk
borne disease outbreaks all over the world, also in Norway.
During this work, we observed that the prevalence of the three examined
bacteria were high in the environment at the examined farms. In addition, 7%
of the milk filters were contaminated by STEC, 13% by L. monocytogenes and
4% by Campylobacter spp. Four of the STEC isolates detected were eaepositive,
which is associated with the capability to cause severe human
disease. One of the eae-positive STEC isolates were collected from a milk
filter, which strongly indicate that Norwegian raw milk may contain potential
pathogenic STEC.
To further assess the possibilities of getting ill by STEC after consuming raw
milk, we examined the growth of the four eae-positive STEC isolates in raw milk at different temperatures. All four isolates seemed to have ability to multiply in raw milk at 8°C, and one isolate had significant growth after 72 hours. Incubation at 6°C seemed to reduce the number of bacteria during the
first 24 hours before cell death stopped. These findings highlight the
importance of stable refrigerator temperatures, preferable < 4°C, for storage
of raw milk.
The L. monocytogenes isolates collected during this study show genetic
similarities to isolates collected from urban and rural environmental
locations, but different clones were predominant in agricultural
environments compared to clinical and food environments. However, the
results indicate that the same clone can persist in a farm over time, and that
milk can be contaminated by L. monocytogenes clones present in farm
environment.
Despite testing small volumes (25 mL) of milk, we were able to isolate both
STEC and Campylobacter spp. directly from raw milk. A proportion of 3% of
the bulk tank milk and teat milk samples were contaminated by
Campylobacter spp. and one STEC was isolated from bulk tank milk. L
monocytogenes was not detected in bulk tank milk, nor in teat milk samples.
The agricultural evolvement during the past decades have led to larger
production units and new food safety challenges. Dairy cattle production in
Norway is in a current transition from tie-stall housing with conventional
pipeline milking systems, to modern loose housing systems with robotic
milking. The occurrence of the three pathogens in this project were higher in
samples collected from farms with loose housing compared to those with tiestall
housing.
Pasteurization of cow’s milk is a risk reducing procedure to protect
consumers from microbial pathogens and in most EU countries, commercial
distribution of unpasteurized milk is legally restricted. Together, the results
presented in this thesis show that the animal housing may influence the level
of pathogenic bacteria in the raw milk and that ingestion of Norwegian raw
cow’s milk may expose consumers to pathogenic bacteria which can cause
severe disease, especially in children, elderly and in persons with underlying
diseases. The results also highlight the importance of storing raw milk at low
temperatures between milking and consumption.Å spise mat som er mindre prosessert og mer «naturlig» er en pågående
trend i Norge og i andre deler av verden. Interessen for å drikke melk som
ikke er varmebehandlet, såkalt rå melk, er også økende. I Norge er det påbudt
å pasteurisere melk før kommersielt salg for å beskytte forbrukeren mot
sykdomsfremkallende mikroorganismer. Fagfolk advarer mot å drikke rå
melk, og påpeker risikoen for å bli syk av patogene bakterier som kan finnes i
melken.
I denne avhandlingen undersøker vi den potensielle risikoen det medfører å
drikke upasteurisert melk fra Norge. I tillegg til å samle inn tankmelk- og
speneprøver fra melkegårder i sørøst Norge, samlet vi også miljøprøver fra
de samme gårdene for å kartlegge forekomst og for å identifisere potensielle
mattrygghetsrisikoer i melkeproduksjonen. Alle prøvene ble analysert for de
zoonotiske sykdomsfremkallende bakteriene Listeria monocytogenes,
Campylobacter spp., og Shiga toksin-produserende Escherichia coli (STEC).
Kyr kan være friske smittebærere av disse bakteriene, som dermed kan
etablere et reservoar på gårdene. Bakteriene kan overføres fra gårdsmiljøet
til melkekjeden og dermed utfordre mattryggheten. Disse bakteriene har
forårsaket melkebårne sykdomsutbrudd over hele verden, også i Norge.
Campylobacter spp. og STEC har lav infeksiøs dose, som vil si at man kan bli
syk selv om man bare inntar et lavt antall bakterieceller. L. monocytogenes
kan gi sykdommen listeriose, en av de mest alvorlige matbårne zoonotiske
sykdommene vi har i den vestlige verden.
Resultater fra denne oppgaven viser en høy forekomst av de tre patogenene i
gårdsmiljøet. I tillegg var 7% av melkefiltrene vi testet positive for STEC, 13%
positive for L. monocytogenes og 4% positive for Campylobacter spp.. Fire av
STEC isolatene bar genet for Intimin, eae, som er ansett som en viktig
virulensfaktor som øker sjansen for alvorlig sykdom. Ett av de eae-positive
isolatene ble funnet i et melkefilter, noe som indikerer at norsk rå melk kan
inneholde patogene STEC. For å videre vurdere risikoen for å bli syk av STEC
fra rå melk undersøkte vi hvordan de fire eae-positive isolatene vokste i rå
melk lagret ved forskjellige temperaturer. For alle isolatene økte antall
bakterier etter lagring ved 8°C, og for et isolat var veksten signifikant. Etter
lagring ved 6°C ble antallet bakterier redusert de første 24 timene, deretter
stoppet reduksjonen i antall bakterier. Disse resultatene viser hvor viktig det
er å ha stabil lav lagringstemperatur for rå melk, helst < 4°C.
L. monocytogenes isolatene som ble samlet inn fra melkegårdene viste
genetiske likheter med isolater samlet inn fra urbane og rurale miljøer rundt
omkring i Norge. Derimot var kloner som dominerte i landbruksmiljøet
forskjellige fra kliniske isolater og isolater fra matproduksjonslokaler. Videre
så man at en klone kan persistere på en gård over tid og at melk kan
kontamineres av L. monocytogenes kloner som er til stede i gårdsmiljøet.
Til tross for små testvolum av tankmelken (25 mL) fant vi både STEC og
Campylobacter spp. i melkeprøvene. 3% av tankmelkprøvene og
speneprøvene var positive for Campylobacter spp. og ett STEC isolat ble
funnet i tankmelk. L. monocytogenes ble ikke funnet direkte i melkeprøvene.
Landbruket i Norge er i stadig utvikling der besetningene blir større, men
færre. Melkebesetningene er midt i en overgang der tradisjonell oppstalling
med melking på bås byttes ut med løsdriftssystemer og melkeroboter.
Forekomsten av de tre patogenene funnet i denne studien var høyere i
besetningene med løsdrift sammenliknet med besetningene som hadde
melkekyrne oppstallet på bås.
Pasteurisering er et viktig forebyggende tiltak for å beskytte konsumenter fra
mikrobielle patogener, og i de fleste EU-land er kommersielt salg av rå melk
juridisk begrenset. Denne studien viser at oppstallingstype kan påvirke
nivåene av patogene bakterier i gårdsmiljøet og i rå melk. Inntak av rå melk
kan eksponere forbruker for patogene bakterier som kan gi alvorlig sykdom,
spesielt hos barn, eldre og personer med underliggende sykdommer.
Resultatene underbygger viktigheten av å pasteurisere melk for å sikre
mattryggheten, og at det er avgjørende å lagre rå melk ved kontinuerlig lave
temperaturer for å forebygge vekst av zoonotiske patogener
Anuário científico da Escola Superior de Tecnologia da Saúde de Lisboa - 2021
É com grande prazer que apresentamos a mais recente edição (a 11.ª) do Anuário Científico da Escola Superior de Tecnologia da Saúde de Lisboa. Como instituição de ensino superior, temos o compromisso de promover e incentivar a pesquisa científica em todas as áreas do conhecimento que contemplam a nossa missão. Esta publicação tem como objetivo divulgar toda a produção científica desenvolvida pelos Professores, Investigadores, Estudantes e Pessoal não Docente da ESTeSL durante 2021. Este Anuário é, assim, o reflexo do trabalho árduo e dedicado da nossa comunidade, que se empenhou na produção de conteúdo científico de elevada qualidade e partilhada com a Sociedade na forma de livros, capítulos de livros, artigos publicados em revistas nacionais e internacionais, resumos de comunicações orais e pósteres, bem como resultado dos trabalhos de 1º e 2º ciclo. Com isto, o conteúdo desta publicação abrange uma ampla variedade de tópicos, desde temas mais fundamentais até estudos de aplicação prática em contextos específicos de Saúde, refletindo desta forma a pluralidade e diversidade de áreas que definem, e tornam única, a ESTeSL. Acreditamos que a investigação e pesquisa científica é um eixo fundamental para o desenvolvimento da sociedade e é por isso que incentivamos os nossos estudantes a envolverem-se em atividades de pesquisa e prática baseada na evidência desde o início dos seus estudos na ESTeSL. Esta publicação é um exemplo do sucesso desses esforços, sendo a maior de sempre, o que faz com que estejamos muito orgulhosos em partilhar os resultados e descobertas dos nossos investigadores com a comunidade científica e o público em geral. Esperamos que este Anuário inspire e motive outros estudantes, profissionais de saúde, professores e outros colaboradores a continuarem a explorar novas ideias e contribuir para o avanço da ciência e da tecnologia no corpo de conhecimento próprio das áreas que compõe a ESTeSL. Agradecemos a todos os envolvidos na produção deste anuário e desejamos uma leitura inspiradora e agradável.info:eu-repo/semantics/publishedVersio
The effects of dairy foods intakes on weight change and fracture risk during critical life stages in women
Menopause and pregnancy are crucial events in women’s lives because women experience a series of physical and psychological changes at these stages. One of the most critical challenges is excessive weight gain during both of these stages, which could contribute to various adverse health events in their later lives. In addition to weight gain, another critical health concern that women face is fragility-related factures. The rate of fragility fractures begins rising in women during their 40s and increases to the end of life. Fractures result in impaired mobility and hospitalization, which can decrease the life quality of women significantly. Identification of modifiable dietary risk factors for excessive weight gain and fracture risk is crucial. The objectives of this dissertation are to estimate the independent effects of total dairy and individual dairy foods (e.g., yogurt, milk, and cheese), alone and in combination with overall diet patterns, physical activity, and other lifestyle factors, on three outcomes among women: weight change during the menopausal transition, weight retention after pregnancy, and risk of fragility-related fractures throughout mid-life and older adult years.
Data from two prospective studies of nurses were used: Nurses’ Health Study I (NHS I) and Nurses’ Health Study II (NHS II). NHS II was used for both weight change analyses, while NHS was used for the fracture analyses. The first specific aim for the analysis of weight change during the menopausal transition was to investigate the effects of total dairy, yogurt, milk, and cheese intakes on menopausal weight change (N = 35,177) and risk of obesity (N = 38,892) among women in NHS II. Weights were self-reported in biennial questionnaires. Diet was assessed with food frequency questionnaires (FFQ) every 4 years. Generalized estimating equations were used to assess the adjusted mean weight change using repeated measures of weight change. Cox proportional hazards models were used to estimate risk of obesity, controlling for confounding.
The second specific aim relates to the postpartum weight change analyses and were to investigate the effects of total dairy, yogurt, milk, and cheese intakes on postpartum weight retention (N = 18,366) and risk of postpartum obesity (N = 17,126) among women in the NHS II. Generalized linear models were used to assess postpartum weight change as continuous outcomes and multivariable models with a Poisson distribution were used to estimate risk of postpartum obesity.
The third specific aim was for the fragility fracture analyses and included investigating the effects of total dairy, yogurt, milk, and cheese on fragility fractures of the hip, wrist, and vertebrae in women ages 40 years and older in NHS I. In total, there are 99,072 women included. Fractures at the wrist and hip were self-reported. For vertebral fractures, we relied on medical record confirmed cases. Proportional hazards models were used to estimate risk of first fracture (including wrist, hip, or vertebral fractures).
Results associated with the first aims suggested that more than 2 servings per week (s/w) of yogurt led to consistently less weight gain than that observed in women consuming less than 1 serving per month (s/m) throughout the menopausal transition. Further, this same yogurt intake was associated with a 31% reduced obesity risk (95% CI: 0.64 - 0.74) after adjusting for potential confounders and baseline body mass index (BMI). Higher total dairy intake was also associated with less obesity risk, but the effect was somewhat weaker than that for yogurt. There was a U-shaped relation between milk consumption and obesity risk during perimenopause. Moderate (0.5 s/d -< 1 s/d vs. < 0.5 s/d) milk consumption reduced obesity risk by 17% (95% CI: 0.78 - 0.89), while higher milk (≥1 s/d vs. < 0.5 s/d) consumption led to a marginally statistically significant 6% higher obesity risk. Cheese intake was not associated with obesity risk in perimenopausal women.
In the postpartum weight retention analyses, women who consumed moderate amounts of yogurt (1 s/m -< 2 s/w) and higher amounts of yogurt (≥ 2 s/w) had a 0.38 lb and 0.63 lb reduction in postpartum weight retention, respectively, than those who rarely consumed yogurt (< 1 s/m). Moderate and higher cheese intakes were associated with 0.30 lb and 0.64 lb less postpartum weight retention, respectively, than lower cheese intake (< 2 s/w). In the obesity analysis, moderate (1 s/m -< 2 s/w) and higher yogurt (≥ 2 s/w) intakes were associated with 20% (95%: 0.69 - 0.93) and 16% (95%: 0.69 - 1.02) reduced risks of postpartum obesity, but the association was weakened by adjusting for pre-pregnancy BMI. Women with higher levels of activity and higher yogurt intakes had a 39% (95%: 0.50 - 0.74) lower risk of obesity. Higher Alternative Healthy Eating Index 2010 (AHEI) scores alone were associated with a statistically significantly lower obesity risk.
Results from our fracture analyses found that women who consumed more than 2 s/d of total dairy had a 19% (95% CI: 0.67 - 0.98) lower fracture risk than those who consumed less than 1 s/w. In terms of individual dairy products, 2 s/d of milk were associated with a 14% (95% CI: 0.77 - 0.95) reduction in fracture risk compared with lower milk consumption (<1 s/w). Higher cheese (≥ 1 s/d vs. < 1 s/w) intake was associated with a non-statistically significant 9% (95% CI: 0.81 - 1.02) reduction in fracture risk. No association was found between yogurt consumption and fracture. In stratified analysis, the intakes of calcium, vitamin D, and protein from non-dietary sources did not modify the inverse association between total dairy or milk intake and fracture risk.
In summary, the findings of this dissertation suggested that greater yogurt consumption was inversely associated with weight change during menopausal transition and after pregnancy while intakes of total dairy and milk had beneficial effects on the risk of fragility fractures among women ages 40 years and older
Decoding spatial location of attended audio-visual stimulus with EEG and fNIRS
When analyzing complex scenes, humans often focus their attention on an object at a particular spatial location in the presence of background noises and irrelevant visual objects. The ability to decode the attended spatial location would facilitate brain computer interfaces (BCI) for complex scene analysis. Here, we tested two different neuroimaging technologies and investigated their capability to decode audio-visual spatial attention in the presence of competing stimuli from multiple locations. For functional near-infrared spectroscopy (fNIRS), we targeted dorsal frontoparietal network including frontal eye field (FEF) and intra-parietal sulcus (IPS) as well as superior temporal gyrus/planum temporal (STG/PT). They all were shown in previous functional magnetic resonance imaging (fMRI) studies to be activated by auditory, visual, or audio-visual spatial tasks. We found that fNIRS provides robust decoding of attended spatial locations for most participants and correlates with behavioral performance. Moreover, we found that FEF makes a large contribution to decoding performance. Surprisingly, the performance was significantly above chance level 1s after cue onset, which is well before the peak of the fNIRS response.
For electroencephalography (EEG), while there are several successful EEG-based algorithms, to date, all of them focused exclusively on auditory modality where eye-related artifacts are minimized or controlled. Successful integration into a more ecological typical usage requires careful consideration for eye-related artifacts which are inevitable. We showed that fast and reliable decoding can be done with or without ocular-removal algorithm. Our results show that EEG and fNIRS are promising platforms for compact, wearable technologies that could be applied to decode attended spatial location and reveal contributions of specific brain regions during complex scene analysis
Identifying and responding to people with mild learning disabilities in the probation service
It has long been recognised that, like many other individuals, people with learningdisabilities find their way into the criminal justice system. This fact is not disputed. Whathas been disputed, however, is the extent to which those with learning disabilities arerepresented within the various agencies of the criminal justice system and the ways inwhich the criminal justice system (and society) should address this. Recently, social andlegislative confusion over the best way to deal with offenders with learning disabilities andmental health problems has meant that the waters have become even more muddied.Despite current government uncertainty concerning the best way to support offenders withlearning disabilities, the probation service is likely to continue to play a key role in thesupervision of such offenders. The three studies contained herein aim to clarify the extentto which those with learning disabilities are represented in the probation service, toexamine the effectiveness of probation for them and to explore some of the ways in whichprobation could be adapted to fit their needs.Study 1 and study 2 showed that around 10% of offenders on probation in Kent appearedto have an IQ below 75, putting them in the bottom 5% of the general population. Study 3was designed to assess some of the support needs of those with learning disabilities in theprobation service, finding that many of the materials used by the probation service arelikely to be too complex for those with learning disabilities to use effectively. To addressthis, a model for service provision is tentatively suggested. This is based on the findings ofthe three studies and a pragmatic assessment of what the probation service is likely to becapable of achieving in the near future
Mathematical models to evaluate the impact of increasing serotype coverage in pneumococcal conjugate vaccines
Of over 100 serotypes of Streptococcus pneumoniae, only 7 were included in the first pneumo- coccal conjugate vaccine (PCV). While PCV reduced the disease incidence, in part because of a herd immunity effect, a replacement effect was observed whereby disease was increasingly caused by serotypes not included in the vaccine. Dynamic transmission models can account for these effects to describe post-vaccination scenarios, whereas economic evaluations can enable decision-makers to compare vaccines of increasing valency for implementation. This thesis has four aims. First, to explore the limitations and assumptions of published pneu- mococcal models and the implications for future vaccine formulation and policy. Second, to conduct a trend analysis assembling all the available evidence for serotype replacement in Europe, North America and Australia to characterise invasive pneumococcal disease (IPD) caused by vaccine-type (VT) and non-vaccine-types (NVT) serotypes. The motivation behind this is to assess the patterns of relative abundance in IPD cases pre- and post-vaccination, to examine country-level differences in relation to the vaccines employed over time since introduction, and to assess the growth of the replacement serotypes in comparison with the serotypes targeted by the vaccine. The third aim is to use a Bayesian framework to estimate serotype-specific invasiveness, i.e. the rate of invasive disease given carriage. This is useful for dynamic transmission modelling, as transmission is through carriage but a majority of serotype-specific pneumococcal data lies in active disease surveillance. This is also helpful to address whether serotype replacement reflects serotypes that are more invasive or whether serotypes in a specific location are equally more invasive than in other locations. Finally, the last aim of this thesis is to estimate the epidemiological and economic impact of increas- ing serotype coverage in PCVs using a dynamic transmission model. Together, the results highlight that though there are key parameter uncertainties that merit further exploration, divergence in serotype replacement and inconsistencies in invasiveness on a country-level may make a universal PCV suboptimal.Open Acces
Discovering the hidden structure of financial markets through bayesian modelling
Understanding what is driving the price of a financial asset is a question that is currently mostly unanswered. In this work we go beyond the classic one step ahead prediction and instead construct models that create new information on the behaviour of these time series. Our aim is to get a better understanding of the hidden structures that drive the moves of each financial time series and thus the market as a whole.
We propose a tool to decompose multiple time series into economically-meaningful variables to explain the endogenous and exogenous factors driving their underlying variability. The methodology we introduce goes beyond the direct model forecast. Indeed, since our model continuously adapts its variables and coefficients, we can study the time series of coefficients and selected variables. We also present a model to construct the causal graph of relations between these time series and include them in the exogenous factors.
Hence, we obtain a model able to explain what is driving the move of both each specific time series and the market as a whole. In addition, the obtained graph of the time series provides new information on the underlying risk structure of this environment. With this deeper understanding of the hidden structure we propose novel ways to detect and forecast risks in the market. We investigate our results with inferences up to one month into the future using stocks, FX futures and ETF futures, demonstrating its superior performance according to accuracy of large moves, longer-term prediction and consistency over time. We also go in more details on the economic interpretation of the new variables and discuss the created graph structure of the market.Open Acces
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