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Transfer learning deals with how systems can quickly adapt themselves to new situations, tasks and environments. It gives machine learning systems the ability to leverage auxiliary data and models to help solve target problems when there is only a small amount of data available. This makes such systems more reliable and robust, keeping the machine learning model faced with unforeseeable changes from deviating too much from expected performance. At an enterprise level, transfer learning allows knowledge to be reused so experience gained once can be repeatedly applied to the real world. For example, a pre-trained model that takes account of user privacy can be downloaded and adapted at the edge of a computer network. This self-contained, comprehensive reference text describes the standard algorithms and demonstrates how these are used in different transfer learning paradigms. It offers a solid grounding for newcomers as well as new insights for seasoned researchers and developers.
We present studies of the solidification of binary aqueous solutions that undergo time-periodic cooling from below. We develop an experiment for solidification of aqueous
$\text{NH}_{4}\text{Cl}$
solutions, where the temperature of the cooling boundary is modulated as a simple periodic function of time with independent variations of the modulation amplitude and frequency. The thickness of the mushy layer exhibits oscillations about the background growth obtained for constant cooling. We consider the deviation given by the difference between states with modulated and fixed cooling, which increases when the modulation amplitude increases but decreases with increasing modulation frequency. At early times, the deviation amplitude is consistent with a scaling argument for growth with quasi-steady modulation. In situ measurements of the mush temperature reveal thermal waves propagating through the mushy layer, with amplitude decaying with height within the mushy layer, whilst the phase lag behind the cooling boundary increases with height. This also leads to phase lags in the variation of the mushy-layer thickness compared to the boundary cooling. There is an asymmetry of the deviation of mushy-layer thickness: during a positive modulation (where the boundary temperature increases at the start of a cycle) the peak thickness deviation has a greater magnitude than the troughs in a negative modulation mode (where the boundary temperature decreases at the start of the cycle). A numerical model is formulated to describe mushy-layer growth with constant bulk concentration and turbulent heat transport at the mush–liquid interface driven by compositional convection associated with a finite interfacial solid fraction. The model recovers key features of the experimental results at early times, including the propagation of thermal waves and oscillations in mushy-layer thickness, although tends to overpredict the mean thickness.
We report an experimental study of the distributions of temperature and solid fraction of growing
$\text{NH}_{4}\text{Cl}$
–
$\text{H}_{2}\text{O}$
mushy layers that are subjected to periodical cooling from below, focusing on late-time dynamics where the mushy layer oscillates about an approximate steady state. Temporal evolution of the local temperature
$T(z,t)$
at various heights in the mush demonstrates that the temperature oscillations of the bottom cooling boundary propagate through the mushy layer with phase delays and substantial decay in the amplitude. As the initial concentration
$C_{0}$
increases, we show that the decay rate of the thermal oscillation with height also decreases, and the propagation speed of the oscillation phase increases. We interpret this as a result of the solid fraction increasing with
$C_{0}$
, which enhances the thermal conductivity but reduces the specific heat of the mushy layer. We present a new methodology to determine the distribution of solid fraction
$\unicode[STIX]{x1D719}(z)$
in mushy layers for various
$C_{0}$
, using only measurements of the temperature
$T(z,t)$
. The method is based on the phase behaviour during thermal modulation, and opens up a new approach for inferring mushy-layer properties in geophysical and engineering settings, where direct measurements are challenging. In our experiments, profiles of the solid fraction
$\unicode[STIX]{x1D719}(z)$
exhibit a cliff–ramp–cliff structure with large vertical gradients of
$\unicode[STIX]{x1D719}$
near the mush–liquid interface and also near the bottom boundary, but much more gradual variation in the interior of the mushy layer. Such a profile structure is more pronounced for higher initial concentration
$C_{0}$
. For very low concentration, the solid fraction appears to be linearly dependent on the height within the mush. The volume-average of the solid fraction, and the local fluctuations in
$\unicode[STIX]{x1D719}(z)$
both increase as
$C_{0}$
increases. We suggest that the fast increase of
$\unicode[STIX]{x1D719}(z)$
near the bottom boundary is possibly due to diffusive transport of solute away from the bottom boundary and the depletion of solute content near the basal region.
Whether borderline personality disorder (BPD) and bipolar disorder are the same or different disorders lacks consistency.
Aims
To detect whether grey matter volume (GMV) and grey matter density (GMD) alterations show any similarities or differences between BPD and bipolar disorder.
Method
Web-based publication databases were searched to conduct a meta-analysis of all voxel-based studies that compared BPD or bipolar disorder with healthy controls. We included 13 BPD studies (395 patients with BPD and 415 healthy controls) and 47 bipolar disorder studies (2111 patients with bipolar disorder and 3261 healthy controls). Peak coordinates from clusters with significant group differences were extracted. Effect-size signed differential mapping meta-analysis was performed to analyse peak coordinates of clusters and thresholds (P < 0.005, uncorrected). Conjunction analyses identified regions in which disorders showed common patterns of volumetric alteration. Correlation analyses were also performed.
Results
Patients with BPD showed decreased GMV and GMD in the bilateral medial prefrontal cortex network (mPFC), bilateral amygdala and right parahippocampal gyrus; patients with bipolar disorder showed decreased GMV and GMD in the bilateral medial orbital frontal cortex (mOFC), right insula and right thalamus, and increased GMV and GMD in the right putamen. Multi-modal analysis indicated smaller volumes in both disorders in clusters in the right medial orbital frontal cortex. Decreased bilateral mPFC in BPD was partly mediated by patient age. Increased GMV and GMD of the right putamen was positively correlated with Young Mania Rating Scale scores in bipolar disorder.
Conclusions
Our results show different patterns of GMV and GMD alteration and do not support the hypothesis that bipolar disorder and BPD are on the same affective spectrum.
Previous studies have inferred a strong genetic component in schizophrenia. However, the genetic variants involved in the susceptibility to schizophrenia remain unclear.
Aims
To detect potential gene pathways and networks associated with schizophrenia, and to explore the relationship between common and rare variants in these pathways and abnormal white matter integrity in schizophrenia.
Method
The analysis included 100 first-episode treatment-naïve patients with schizophrenia and 140 healthy controls. A network-based analysis was carried out on the data collected from the Psychiatric Genomics Consortium Phase I (PGC-I). Based on our genome-wide association study and whole-exome sequencing data-sets, we performed a gene-set analysis to detect associations between the combining effects of common and rare genetic variants and abnormal white matter integrity in schizophrenia.
Results
Patients had significantly reduced functional anisotropy in the left and right anterior cingulate cortex, left and right precuneus and extra-nuclear (t = 4.61–5.10, PFDR < 0.01), compared with controls. Generated from co-expression network analysis of the PGC-1 summary statistics of schizophrenia, a subnetwork of 207 genes associated with schizophrenia was identified (P < 0.01), and 176 genes were co-expressed in four gene modules. Functional enrichment analysis for genes in each module revealed that the yellow module was enriched with highly co-expressed, innate immune response genes. Furthermore, rare variants of enriched genes in the yellow module were associated with reduced functional anisotropy in the left anterior cingulate cortex (P = 0.006; Padjusted = 0.024) in patients only.
Conclusions
The pathogenesis of schizophrenia may be substantially influenced by genes involved in the immune system, via both pathway and network.
To eliminate the toxic effect of chemotherapy drug of lobaplatin (LBP) on body tissue in liver cancer therapy, this work prepared a nanodrug carrier based on polyethylene glycol-modified carbon nanotubes (PEG–CNTs) and then constructed a targeted drug delivery system (LBP–PEG–CNTs) by loading LBP on PEG–CNTs. Fluorescein isothiocyanate (FITC) was used to label PEG–CNTs to observe the cellular uptake of PEG–CNTs. In addition, the inhibitions of LBP–PEG–CNTs on HepG2 cells were investigated. The results show that the FITC-labeled PEG–CNTs have good cell penetrability; meanwhile, LBP–PEG–CNTs have good stability, pH-controlled release property, and high inhibition rate on HepG2 cells. To be specific, 80% of LBP is released under physiological conditions of liver cancer cells at pH 5.0, and LBP–PEG–CNTs show a high inhibition rate of 77.86% on HepG2 cells, demonstrating that they have targeted, pH-controlled release and inhibition properties on HepG2 cells.
This study examined the mediating effects of future social expectations and interpersonal distrust on the relationship between individual relative deprivation and intention to rebel. Data were gathered from 807 people from multiple occupational backgrounds in a municipality in southwest China. Structural equation modelling showed that individual relative deprivation predicted intention to rebel directly and also that it predicted intention to rebel indirectly via negative future social expectations, interpersonal distrust, and a chain mediating effect of negative future social expectations and interpersonal distrust. These results highlight the importance of the associations between future social expectations and interpersonal distrust with intention to rebel in people who report relative deprivation. The findings also indicate that prevention and intervention programs related to relative deprivation and intention to rebel in China are worthy of further research.
China's trade with Taiwan has a political motive: winning the hearts and minds of the Taiwanese people. The effectiveness of China's economic statecraft can be examined in the Syuejia (Xuejia) case, where Taiwan put up strong resistance to the generous benefits offered by China. This article investigates the political implications of the Chinese-designed contract farming programme in Syuejia and argues that if economic favours are delivered, and positive impressions also created, political attitudes can be revised. Without these two prerequisites, however, replicating the Syuejia results elsewhere and thus disturbing the cross-Strait status quo will be difficult. When put in a theoretical context, the changes in the political landscape of Syuejia illustrate the interplay of economic interests and political identity.
Polystyrene spheres were found to be an effective assisted material in the growth of indium-tin-oxide (ITO) nanowire networks, bearing low temperature, high purity, and good control of size. The temperature and time of growth were studied to achieve ITO nanowire networks with high transmission and low resistivity. When prepared by PS spheres of 670 nm dia. for 15 min at 300 °C, the transmittance is above 90% after the wave length of 400 nm, and the sheet resistance is ∼200 Ω/□. Polystyrene-assisted ITO nanowires showed the high degree of crystallinity with lattice fringes, and well coincided cubic phase of In2O3. The density of ITO nanowire networks were controlled by polystyrene spheres and the residual polystyrene was removed by thermal annealing. ITO nanowire networks open new opportunities for optoelectronic devices needing special morphology for the improvement of light extraction efficiency, and as a new type of conductive film, which have an even broad application arena.
An effective multiplex real-time polymerase chain reaction (PCR) assay for the simultaneous detection of three major pathogens, Nosema bombycis Nägeli (Microsporidia: Nosematidae), Bombyx mori nucleopolyhedrovirus (Baculoviridae: genus Alphabaculovirus) (NPV), and Bombyx mori densovirus (Parvoviridae: genus Iteravirus) (DNV), in silkworms (Bombyx mori (Linnaeus); Lepidoptera: Bombycidae) was developed in this study. Polymerase chain reaction and real-time PCR tests and basic local alignment search tool searches revealed that the primers and probes used in this study had high specificities for their target species. The ability of each primer/probe set to detect pure pathogen DNA was determined using a plasmid dilution panel, in which under optimal conditions the multiplex real-time PCR assay showed high efficiency in the detection of three mixed target plasmids with a detection limit of 8.5×103 copies for N. bombycis and Bombyx mori NPV (BmNPV) and 8.5×104 copies for Bombyx mori DNV (BmDNV). When the ability to detect these three pathogens was examined in artificially inoculated silkworms, our method presented a number of advantages over traditional microscopy, including specificity, sensitivity, and high-throughput capabilities. Under the optimal volume ratio for the three primer/probe sets (3:2:2=N. bombycis:BmNPV:BmDNV), the multiplex real-time PCR assay showed early detection of BmNPV and BmDNV by day 1 post inoculation using DNA templates of the three pathogens in various combinations from individually infected silkworms; the early detection of N. bombycis was possible by day 3 post inoculation using the DNA isolated from the midgut of N. bombycis-infected silkworms.
A series of oxidation experiments were carried out on these novel γ/γ′-strengthened cobalt-based alloys of the systems Co–9Al–10W and Co–9Al–10W–0.02X (X = La, Ce, Dy, Y) at 900 °C. The appropriate amounts’ addition of rare earth elements leads to improved oxidation properties at 900 °C, especially La elements show the best oxidation resistance (129.008 mg/cm2). However, the base Co–9Al–10W alloy shows the worst oxidation performance (151.544 mg/cm2). Multilayer oxide layers formed during the oxidation process, the outer were mainly CoO and Co3O4 oxides, and the middle layer contained complex oxides (containing Co, Al, and W). The inner layer consists of little discontinuous oxides, included few Al2O3 oxides. There existed a different crack width and the base alloy had the widest crack. Moreover, there exists a phase transformation (γ/γ′ to γ/Co3W) at the interface between oxide film and substrate.
The isothermal oxidation experiments were carried out on several new γ/γ′-strengthened cobalt-base alloys Co–Al–W–4Cr–0.02X (X = La, Ce, Dy, Y) at 900 and 800 °C. Due to an appropriate content of additional elements, the change in the morphology occurred and it significantly improved the oxidation resistance compared with those without Cr, among which the one with La elements shows the best oxidation resistance. Multiple oxide layers are also formed during the oxidation process, with CoWO4 and CoAl2O4 phases in the outer layer, and Cr, Al, W, and Co (e.g., Cr2O3) in the middle layer. The inner layer consists of some Al2O3 oxides, while more protective Al2O3 oxide was formed, esp. at the temperature of 800 °C. Both Cr2O3 and Al2O3 oxides were effectively protective oxides, which can prevent the intrusion of oxygen into the alloy substrate. Moreover, a phase transformation (γ/γ′ to γ/Co3W) was observed at the interface between oxide layer and substrate.
Choline and betaine are essential nutrients involved in one-carbon metabolism and have been hypothesised to affect breast cancer risk. Functional polymorphisms in genes encoding choline-related one-carbon metabolism enzymes, including phosphatidylethanolamine N-methyltransferase (PEMT), choline dehydrogenase (CHDH) and betaine-homocysteine methyltransferase (BHMT), have important roles in choline metabolism and may thus interact with dietary choline and betaine intake to modify breast cancer risk. This study aimed to investigate the interactive effect of polymorphisms in PEMT, BHMT and CHDH genes with choline/betaine intake on breast cancer risk among Chinese women. This hospital-based case–control study consecutively recruited 570 cases with histologically confirmed breast cancer and 576 age-matched (5-year interval) controls. Choline and betaine intakes were assessed by a validated FFQ, and genotyping was conducted for PEMT rs7946, CHDH rs9001 and BHMT rs3733890. OR and 95 % CI were estimated using unconditional logistic regression. Compared with the highest quartile of choline intake, the lowest intake quartile showed a significant increased risk of breast cancer. The SNP PEMT rs7946, CHDH rs9001 and BHMT rs3733890 had no overall association with breast cancer, but a significant risk reduction was observed among postmenopausal women with AA genotype of BHMT rs3733890 (OR 0·49; 95 % CI 0·25, 0·98). Significant interactions were observed between choline intake and SNP PEMT rs7946 (Pinteraction=0·029) and BHMT rs3733890 (Pinteraction=0·006) in relation to breast cancer risk. Our results suggest that SNP PEMT rs7946 and BHMT rs3733890 may interact with choline intake on breast cancer risk.
Psychiatric disorders such as schizophrenia and major depressive disorder
(MDD) are likely to be caused by multiple susceptibility genes, each with
small effects in increasing the risk of illness. Identifying DNA variants
associated with schizophrenia and MDD is a crucial step in understanding
the pathophysiology of these disorders.
Aims
To investigate whether the SP4 gene plays a significant
role in schizophrenia or MDD in the Han Chinese population.
Method
We focused on nine single nucleotide polymorphisms (SNPs) harbouring the
SP4 gene and carried out case–control studies in 1235
patients with schizophrenia, 1045 patients with MDD and 1235 healthy
controls recruited from the Han Chinese population.
Results
We found that rs40245 was significantly associated with schizophrenia in
both allele and genotype distributions (Pallele = 0.0005, Pallele = 0.004 after Bonferroni correction; Pgenotype = 0.0023, Pgenotype = 0.0184 after Bonferroni correction). The rs6461563
SNP was significantly associated with schizophrenia in the allele
distributions (Pallele = 0.0033, Pallele = 0.0264 after Bonferroni correction).
Conclusions
Our results suggest that common risk factors in the SP4
gene are associated with schizophrenia, although not with MDD, in the Han
Chinese population.
There are numerous Earth orbiting satellite sensors that provide observations useful in assessing land cover conditions and landscape dynamics. These orbiting sensors measure spatial patterns of reflected and emitted energy from the land surface that can be used to generate geospatial image products of soil, vegetation, water and biogeochemical features. They measure changes over time through their repeat observations across a range of spatial and temporal scales. Satellite imagery extending back to the 1970s now provides a forty-plus year observation data record of dynamic ecosystem conditions and land surface changes. The synoptic coverage, higher-quality and consistency of satellite imagery have greatly improved the mapping of Earth resources compared with aerial photography.
A basic understanding of the variety of sensor designs and their characteristics is beneficial in correctly applying remote sensing tools to achieve various science and resource management objectives (Fig. 6.1). It is also important to know which sensors yield the appropriate type of remote sensing data to best answer specific ecological questions. Various sensor-dependent properties, such as pixel size, spectral bands, temporal repeat period, radiometric fidelity, polarization and viewing geometry are utilized to measure and characterize the Earth's surface. Each sensor system will have unique measurement strengths and limitations in its ability to characterise and retrieve land cover information.
There are many ways to classify the multitude of orbiting sensors and imagery available for ecosystem landscape studies. Important differentiating criteria may include the region of the electromagnetic spectrum (e.g., microwave, thermal, visible, near-infrared) being sensed, whether the energy source is active versus passive, sensor orbital characteristics (e.g., geostationary), frequency of image acquisition and sensor spatial resolution. In this chapter we introduce basic sensor principles, their design and properties, and discuss their respective capabilities and limitations in assessing land cover status, ecological variables, and landscape processes. Examples of the various types of sensor systems used in landscape studies are also highlighted.
Sensor Resolution
The resolution properties of a sensor define the magnitude and extent to which a sensor is able to discriminate variations and changes in landscape properties. In general, improved surface characterisations are achieved with finer resolution imaging capabilities. However, all sensors are limited by resolution constraints and signal noise limitations.
Understanding ecosystem structure and function requires familiarity with the techniques, knowledge and concepts of the three disciplines of plant physiology, remote sensing and modelling. This is the first textbook to provide the fundamentals of these three domains in a single volume. It then applies cross-disciplinary insights to multiple case studies in vegetation and landscape science. A key feature of these case studies is an examination of relationships among climate, vegetation structure and vegetation function, to address fundamental research questions. This book is for advanced students and researchers who need to understand and apply knowledge from the disciplines of plant physiology, remote sensing and modelling. It allows readers to integrate and synthesise knowledge to produce a holistic understanding of the structure, function and behaviour of forests, woodlands and grasslands.