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Controlling cis/trans isomerism of monounsaturated fatty acids via a recombinant cytochrome c-type cis/trans fatty acid isomerase
Get PDFCytochrome c-type cis/trans fatty acid isomerase (CTI) has been proposed to control cis/trans isomerism of unsaturated fats in lipid-related food products. A gene encoding wildtype CTI from Pseudomonas putida KT2440 was introduced into the pET26b/pEC86 co-expression system, and the heme C cofactor was covalently bound into the expressed CTI protein through in vivo cytochrome c maturation. The recombinant CTI, purified from Escherichia coli BL21(DE3), catalyzed the cis/trans isomerization of three edible monounsaturated fatty acids. It exhibited strong substrate selectivity for palmitoleic acid (C16:1, cis-Δ9), reaching an 80.93 ± 1.78% conversion at reaction equilibrium. Notably, its promiscuity for other fatty acids (oleic acid: 29.21 ± 5.01% and cis-vaccenic acid: 51.21 ± 0.05%) was observed. Under the optimum reaction conditions (pH 7.5 and 15 °C), the kinetic parameters (Vmax, Km, and kcat) of CTI were derived as 0.035 mM·min−1, 0.267 mM, and 0.141 sec−1, respectively, and the final catalytic efficiency (kcat/Km) was calculated as 5.26 × 102 M−1·sec−1. Furthermore, structural properties of CTI were analyzed using deep learning-based protein structure prediction, suggesting the potential for specificity variability by altering loop dynamics and helix interactions surrounding the heme-binding motif. The following results would provide theoretical and practical information for CTI enzymes as novel promising industrial catalysts to control cis/trans isomerism of lipids in food products
Panacea or producer? Analysing the relationship between international Law and disaster risk
Get PDFThis thesis seeks to critically analyse the relationship between international law and disaster risk.
Despite the increasing global threat that disasters present, international law’s engagement with
their prevention remains at a relatively nascent stage compared to the development of other
areas of the law. However, the progress that has been made since the United Nation’s
International Decade for Natural Disaster Reduction in the 1990s suggests that international law
is widely viewed as a valuable tool in addressing the issue and reducing the risk of disasters. In
contrast to this, however, relatively little attention has been paid to the ways that international
law itself may also play a role in the creation of disaster risk.
It is here that the project makes an important and original contribution, by interrogating this
presupposition and analysing the ways that international law itself may be culpable in the
creation and exacerbation of risk. Through a novel, compound theoretical lens combining
Marxist and Third World approaches to international law and insights from disaster theory, the
thesis highlights the longstanding complicity of international law in the production of disaster
risk. The thesis draws on understandings of disasters as processes that reach back through time,
and thus begins its analysis with an examination of the early history of international law and the
role of its colonial doctrines in the historic construction of vulnerability and hazards. It then
turns to modern international law, particularly within the realm of international economic law, to
examine the continuing legacies of these early developments and the ongoing role of
international law in disaster risk creation.
Overall, the thesis offers an original contribution to conversations on the connection between
international law and disaster risk. Rather than focusing only on the positive role that
international law can have in the reduction of disaster risk found in the majority of the literature,
it seeks to highlight more pathological aspects of the relationship between the two and the
implications of this. It ultimately concludes that unless the burgeoning field of international
disaster law engages more with such critical accounts of international law and their
understandings of the harm the law produces, then it will remain blind to a major source of
disaster risk creation and be unsuccessful in achieving its normative aims
Online semi-supervised learning in non-stationary environments
Get PDFExisting Data Stream Mining (DSM) algorithms assume the availability of labelled and
balanced data, immediately or after some delay, to extract worthwhile knowledge from the
continuous and rapid data streams. However, in many real-world applications such as
Robotics, Weather Monitoring, Fraud Detection Systems, Cyber Security, and Computer
Network Traffic Flow, an enormous amount of high-speed data is generated by Internet of
Things sensors and real-time data on the Internet. Manual labelling of these data streams
is not practical due to time consumption and the need for domain expertise. Another
challenge is learning under Non-Stationary Environments (NSEs), which occurs due to
changes in the data distributions in a set of input variables and/or class labels. The problem
of Extreme Verification Latency (EVL) under NSEs is referred to as Initially Labelled Non-Stationary Environment (ILNSE). This is a challenging task because the learning algorithms
have no access to the true class labels directly when the concept evolves. Several approaches
exist that deal with NSE and EVL in isolation. However, few algorithms address both issues
simultaneously. This research directly responds to ILNSE’s challenge in proposing two
novel algorithms “Predictor for Streaming Data with Scarce Labels” (PSDSL) and
Heterogeneous Dynamic Weighted Majority (HDWM) classifier. PSDSL is an Online Semi-Supervised Learning (OSSL) method for real-time DSM and is closely related to label
scarcity issues in online machine learning.
The key capabilities of PSDSL include learning from a small amount of labelled data in an
incremental or online manner and being available to predict at any time. To achieve this,
PSDSL utilises both labelled and unlabelled data to train the prediction models, meaning it
continuously learns from incoming data and updates the model as new labelled or
unlabelled data becomes available over time. Furthermore, it can predict under NSE
conditions under the scarcity of class labels. PSDSL is built on top of the HDWM classifier,
which preserves the diversity of the classifiers. PSDSL and HDWM can intelligently switch
and adapt to the conditions. The PSDSL adapts to learning states between self-learning,
micro-clustering and CGC, whichever approach is beneficial, based on the characteristics of
the data stream. HDWM makes use of “seed” learners of different types in an ensemble to
maintain its diversity. The ensembles are simply the combination of predictive models
grouped to improve the predictive performance of a single classifier.
PSDSL is empirically evaluated against COMPOSE, LEVELIW, SCARGC and MClassification
on benchmarks, NSE datasets as well as Massive Online Analysis (MOA) data streams and real-world datasets. The results showed that PSDSL performed significantly better than
existing approaches on most real-time data streams including randomised data instances.
PSDSL performed significantly better than ‘Static’ i.e. the classifier is not updated after it is
trained with the first examples in the data streams. When applied to MOA-generated data
streams, PSDSL ranked highest (1.5) and thus performed significantly better than SCARGC,
while SCARGC performed the same as the Static. PSDSL achieved better average prediction
accuracies in a short time than SCARGC.
The HDWM algorithm is evaluated on artificial and real-world data streams against existing
well-known approaches such as the heterogeneous WMA and the homogeneous Dynamic
DWM algorithm. The results showed that HDWM performed significantly better than WMA
and DWM. Also, when recurring concept drifts were present, the predictive performance of
HDWM showed an improvement over DWM. In both drift and real-world streams,
significance tests and post hoc comparisons found significant differences between
algorithms, HDWM performed significantly better than DWM and WMA when applied to
MOA data streams and 4 real-world datasets Electric, Spam, Sensor and Forest cover. The
seeding mechanism and dynamic inclusion of new base learners in the HDWM algorithms
benefit from the use of both forgetting and retaining the models. The algorithm also
provides the independence of selecting the optimal base classifier in its ensemble depending
on the problem.
A new approach, Envelope-Clustering is introduced to resolve the cluster overlap conflicts
during the cluster labelling process. In this process, PSDSL transforms the centroids’
information of micro-clusters into micro-instances and generates new clusters called
Envelopes. The nearest envelope clusters assist the conflicted micro-clusters and
successfully guide the cluster labelling process after the concept drifts in the absence of true
class labels. PSDSL has been evaluated on real-world problem ‘keystroke dynamics’, and
the results show that PSDSL achieved higher prediction accuracy (85.3%) and SCARGC
(81.6%), while the Static (49.0%) significantly degrades the performance due to changes in
the users typing pattern. Furthermore, the predictive accuracies of SCARGC are found
highly fluctuated between (41.1% to 81.6%) based on different values of parameter ‘k’
(number of clusters), while PSDSL automatically determine the best values for this
parameter
Mindfulness in family communication: an overview of mechanisms, recent findings, and applications
Get PDFElevated evolutionary rates of biting biomechanics reveal patterns of extraordinary craniodental adaptations in some herbivorous dinosaurs
Get PDFAdaptation to specialist ecological niches is a key innovation that has contributed to the evolutionary success of many vertebrate clades, underpinning the acquisition of diverse skull morphologies. Dinosaurs, which dominated Mesozoic terrestrial faunas, acquired herbivory multiple times, and evolution of these herbivorous adaptations is linked to drastic changes in dental and craniomandibular functional morphology, yet whether changes in functionally relevant phenotypic traits occurred more rapidly in herbivorous lineages compared to in carnivorous lineages remains largely untested in a statistical phylogenetic framework. Here, we infer rates of phenotypic evolution using phylogenetic variable‐rate models on relative biting edge (tooth row) lengths of 107 dinosaur taxa to test the hypothesis that the acquisition of herbivory is associated with rapid changes in mandibular biomechanics. We find elevated rates of biomechanical evolution in theropods with foreshortened and beaked skulls (Oviraptorosauria, Limusaurus), as well as in ceratopsians and Diplodocus. The presence and position of a reduced tooth row and increased jaw efficiency unite these high‐rate lineages, indicating selection for greater efficiency in biting biomechanics. Large departures from the isometric scaling of these mandibular characteristics helps explain the differences in evolutionary rates in these clades and those of other herbivorous theropods (Therizinosauria, Ornithomimosauria). Additionally, we hypothesize that extreme ontogenetic changes within species lifetimes may be behind some instances of branch‐wise elevated rates. Thus, we show how exceptional rates of biomechanical evolution can reveal signatures of ecological adaptations within dinosaur lineages as well as within‐species ontogenetic sequences
The effect of the ageing process on the desorption of nonylphenol in black carbon-sediment systems: a kineto-mechanistic and modeling investigation
No full textBlack carbon (BC) exhibits promising potential as a sediment amendment owing to its commendable adsorption capacity for hydrophobic organic contaminants (HOCs), thereby resulting in HOC-laden sediments. Desorption kinetic studies play a crucial role in comprehending the release potential of HOCs from BC-sediment systems. Although the adsorption capacity of BC for HOCs has been found to decrease with aging, there is limited research on its impact on HOC desorption kinetics. In this study, BCs derived from agricultural waste (rice straw carbon, RC) and industrial waste (fly ash carbon, FC), respectively, were used to investigate the desorption kinetics of nonylphenol (NP). Additionally, a predictive model was established using the fitting parameters obtained from the modified two-domain model. The results showed that desorption of NP was divided into three fractions: rapid fraction (Frap), slow fraction (Fslow) and resistant fraction (Fr). BCs significantly decreased, while ageing increased the desorption amount and rate of NP. The performance of RC in controlling NP release was superior to that of FC. The predicted values calculated by the established model exhibit significant positive correlations with the measured values (p < 0.01). Additionally, the correlation analysis between sorption sites and desorption fractions revealed that the concentration of NP in the desorbing fraction was nearly equivalent to that of NP in partition sites within aged sediment/FC-sediment systems. However, the aged RC-sediment systems do not conform well to this rule. In other words, the estimation of NP release risk from sediments with a strong adsorbent would be overestimated, if Frap + Fsolw is considered equivalent to the desorbing fraction
Resting EEG periodic and aperiodic components predict cognitive decline over 10 years
Get PDFMeasures of intrinsic brain function at rest show promise as predictors of cognitive decline in humans, including EEG metrics such as individual alpha peak frequency (IAPF) and the aperiodic exponent, reflecting the strongest frequency of alpha oscillations and the relative balance of excitatory:inhibitory neural activity, respectively. Both IAPF and the aperiodic exponent decrease with age and have been associated with worse executive function and working memory. However, few studies have jointly examined their associations with cognitive function, and none have examined their association with longitudinal cognitive decline rather than cross-sectional impairment. In a preregistered secondary analysis of data from the longitudinal Midlife in the United States (MIDUS) study, we tested whether IAPF and aperiodic exponent measured at rest predict cognitive function (N = 235; age at EEG recording M = 55.10, SD = 10.71) over 10 years. The IAPF and the aperiodic exponent interacted to predict decline in overall cognitive ability, even after controlling for age, sex, education, and lag between data collection timepoints. Post-hoc tests showed that “mismatched” IAPF and aperiodic exponents (e.g., higher exponent with lower IAPF) predicted greater cognitive decline compared to “matching” IAPF and aperiodic exponents (e.g., higher exponent with higher IAPF; lower IAPF with lower aperiodic exponent). These effects were largely driven by measures of executive function. Our findings provide the first evidence that IAPF and the aperiodic exponent are joint predictors of cognitive decline from midlife into old age and thus may offer a useful clinical tool for predicting cognitive risk in aging
Sentence processing in bilingual children: evidence from garden-path sentences
Get PDFResearch in sentence processing in bilingual children is emergent but incomplete as very few studies examine the processing of structurally complex sentences or bilingual children’s real-time interpretation of sentences. One underexplored linguistic feature which can offer insights in this direction are garden-path sentences, i.e., sentences with temporary syntactic ambiguity. These are difficult to process for monolingual children as incremental processing results in an initial misinterpretation and the need for reanalysis. Studies on bilingual children’s processing of garden-path sentences have used paradigms with limited ecological validity and which are not informative about one’s interpretation while listening. This study bridges this gap by investigating the processing of garden-path sentences in bilingual children with the visual-world eye-tracking paradigm. It further explores the role of referential context in the visual stimuli to aid disambiguation. Monolingual and bilingual children aged 8-11 years completed a task similar to Trueswell et al. (1999). The results showed similar difficulty with revising garden-path sentences as evidenced by comprehension accuracy for both groups but only the monolinguals showed real-time garden-path effects in the gaze data. We interpret these findings as a manifestation of slower sentence processing in bilingual children. Both groups made limited use of the referential context to facilitate processing