Isolation, Characterisation and Application of Bacteriophages in Aquaculture

The increasing incidence of infections due to antibiotic resistant bacteria has led to renewed interest in bacteriophages (= phages) and phage therapy. Although phage therapy has been applied to control bacterial diseases in plants, poultry, livestock and humans, its application in aquaculture is still relatively limited. The emergence of phage-resistant bacterial mutants has been considered to be one of the major limitations of phage therapy. This study aimed to (i) isolate and characterise phages; (ii) select phages and their bacterial hosts to set up in vivo phage therapy models with aquaculture animals, and estimate the efficiency of phage therapy; (iii) investigate the generation and characteristics of phage-resistant mutants, and thus estimate the consequence of applying phage therapy when phage-resistant mutants emerge; and (iv) discuss the prospects for application of phages in aquaculture. Two Vibrio isolates and their phages were isolated from a Scottish marine fish farm. Based on the results of conventional phenotype testing and 16S rRNA gene sequencing analysis, the two vibrios, V9 and V13, were identified as Vibrio splendidus and Vibrio cyclitrophicus, respectively. The bacterial characteristics including morphology, temperature and salinity range of growth, production of extracellular enzymes, and the possession of virulence genes were examined. According to the morphological characteristics observed using transmission electron microscopy by negative staining, phage PVS9 of V. splendidus V9 was identified as a myophage, while phage PVC13 of V. cyclitrophicus V13 was identified as a siphophage. The phages could only lyse one bacterial host strain and their genomic DNA was double stranded with a size of ~46 kb. The two Vibrio isolates were found to be non- or of low virulence to rainbow trout, goldsinny wrasse and Artemia in pathogenicity experiments. Thus an in vivo phage therapy model could not be set up using these Vibrio isolates and their phages. Two phages pAS-3 and pAS-6 were isolated using the Aeromonas salmonicida subsp. salmonicida Hooke strain as the host. Phages pAS-3 and pAS-6 had a similar genome size of ~50 kb, and the same relatively narrow host range within A. salmonicida subsp. salmonicida strains. The siphophage pAS-3 formed clear plaques and inhibited A. salmonicida Hooke growth in vitro completely for at least 18 hours when using MOI = 1,000, whereas the podophage pAS-6 formed turbid plaques and weakly inhibited Hooke growth. Rainbow trout exposed by intraperitoneal injection with 0.1 mL of the raw phage preparations at a concentration of 108 PUF mL-1 showed no adverse effects over 14 days. In the phage therapy trial, fish were firstly injected with 1 x 102 CFU fish-1 of A. salmonicida Hooke, then immediately injected with phage preparations of pAS-3 and pAS-6, respectively, using MOI = 10,000. Compared with the control group (which did not receive phage treatment), phage treated groups showed a delay in the time to death, and lower mortalities. However, the mortalities and time to death between phage treated and non-treated groups were not significantly different. Phage-resistant mutants of pathogenic A. salmonicida strain Hooke were induced by repeatedly challenging with phage pAS-3. One of the mutants, termed HM, was chosen to compare the characteristics with the parental wild-type strain Hooke. Test results including the formation of ‘smooth’ colonies on TSA, autoagglutination negative, the formation of creamy colonies on Coomassie Brilliant Blue agar, and the degradation of a thick/furry layered structure on the cell surface indicated a deficiency of the A-layer in the phage-resistant mutant HM. Therefore, it was deduced that the A-layer either directly acted as the receptor of A. salmonicida phage pAS-3, or was affected indirectly by the change of an unknown phage receptor. The greater wax moth larvae model was used to compare the virulence of the phage-resistant mutant HM and the parental wild-type strain Hooke, as it is an ethically acceptable animal model, which has the advantages of being low cost and convenient for injection, and is also a recognised alternative model for bacterial pathogens of fish. The results showed that virulence of the phage-resistant mutant HM did not decline in the greater wax moth larvae model compared with that of the parental wild-type strain Hooke. In conclusion, different approaches were used to isolate and characterise phages from different aquaculture environments for potential use in phage therapy. A rainbow trout model was set up using pathogenic A. salmonicida strain Hooke and two A. salmonicida phages pAS-3 and pAS-6. The use of phage treatment led to lower cumulative mortalities and delay to the time of death, although the differences between the groups were not significant, futher work is required to determine if these phages have potential in phage therapy. The consequence of applying phage therapy when phage-resistant mutants emerge was estimated based on their characteristics and virulence, and no decline in virulence of the phage-resistant mutant from this study indicates the importance of fully testing the virulence of phage-resistant mutants before carrying out large scale field trials of phage therapy. It appears feasible to use phage therapy as an alternative approach to control bacterial infections in aquaculture, but further studies are required to focus on improving effectiveness, and also to overcome the concrete limitations and hurdles in application and commercialisation. Moreover, a broader range of applications of phages in aquaculture should be explored

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Generative Pre-trained Transformer (GPT) models have exhibited exciting progress in capabilities, capturing the interest of practitioners and the public alike. Yet, while the literature on the trustworthiness of GPT models remains limited, practitioners have proposed employing capable GPT models for sensitive applications to healthcare and finance - where mistakes can be costly. To this end, this work proposes a comprehensive trustworthiness evaluation for large language models with a focus on GPT-4 and GPT-3.5, considering diverse perspectives - including toxicity, stereotype bias, adversarial robustness, out-of-distribution robustness, robustness on adversarial demonstrations, privacy, machine ethics, and fairness. Based on our evaluations, we discover previously unpublished vulnerabilities to trustworthiness threats. For instance, we find that GPT models can be easily misled to generate toxic and biased outputs and leak private information in both training data and conversation history. We also find that although GPT-4 is usually more trustworthy than GPT-3.5 on standard benchmarks, GPT-4 is more vulnerable given jailbreaking system or user prompts, potentially due to the reason that GPT-4 follows the (misleading) instructions more precisely. Our work illustrates a comprehensive trustworthiness evaluation of GPT models and sheds light on the trustworthiness gaps. Our benchmark is publicly available at https://decodingtrust.github.io/

Pump-controlled wavelength switchable dissipative soliton mode-locked Yb-doped fiber laser using a 45° tilted fiber grating

We demonstrate a pump-controlled wavelength switchable Yb-doped fiber laser (YDFL) by nonlinear polarization rotation (NPR) for the first time. The polarizer replaced by a 45° tilted fiber grating (45°-TFG) combines with a section of polarization maintaining fiber (PMF) to form a fiber-based birefringent filter. Stable dissipative soliton (DS) with center wavelength of 1068.39 nm is generated under the mode-locked threshold of 277 mW. The operating wavelength switching between 1046.51 nm and 1067.90 nm can be realized via increasing the pump power simply while keeping the polarization controllers (PCs) in a fixed state. The laser maintains stable mode-locking operation at each wavelength, which can be regarded as a type of multi-wavelength ultrafast light source with precise control and integration potential

Human gait recognition using patch distribution feature and locality-constrained group sparse representation

In this paper, we propose a new patch distribution feature (PDF) (i.e., referred to as Gabor-PDF) for human gait recognition. We represent each gait energy image (GEI) as a set of local augmented Gabor features, which concatenate the Gabor features extracted from different scales and different orientations together with the X-Y coordinates. We learn a global Gaussian mixture model (GMM) (i.e., referred to as the universal background model) with the local augmented Gabor features from all the gallery GEIs; then, each gallery or probe GEI is further expressed as the normalized parameters of an image-specific GMM adapted from the global GMM. Observing that one video is naturally represented as a group of GEIs, we also propose a new classification method called locality-constrained group sparse representation (LGSR) to classify each probe video by minimizing the weighted l1, 2 mixed-norm-regularized reconstruction error with respect to the gallery videos. In contrast to the standard group sparse representation method that is a special case of LGSR, the group sparsity and local smooth sparsity constraints are both enforced in LGSR. Our comprehensive experiments on the benchmark USF HumanID database demonstrate the effectiveness of the newly proposed feature Gabor-PDF and the new classification method LGSR for human gait recognition. Moreover, LGSR using the new feature Gabor-PDF achieves the best average Rank-1 and Rank-5 recognition rates on this database among all gait recognition algorithms proposed to date

Spectral Embedded Clustering: A Framework for In-Sample and Out-of-Sample Spectral Clustering

Abstract — Spectral clustering (SC) methods have been successfully applied to many real-world applications. The success of these SC methods is largely based on the manifold assumption, namely, that two nearby data points in the high-density region of a low-dimensional data manifold have the same cluster label. However, such an assumption might not always hold on high-dimensional data. When the data do not exhibit a clear low-dimensional manifold structure (e.g., high-dimensional and sparse data), the clustering performance of SC will be degraded and become even worse than K-means clustering. In this paper, motivated by the observation that the true cluster assignment matrix for high-dimensional data can be always embedded in a linear space spanned by the data, we propose the spectral embedded clustering (SEC) framework, in which a linearity regularization is explicitly added into the objective function of SC methods. More importantly, the proposed SEC framework can naturally deal with out-of-sample data. We also present a new Laplacian matrix constructed from a local regression of each pattern and incorporate it into our SEC framework to capture both local and global discriminative information for clustering. Comprehensive experiments on eight real-world high-dimensional datasets demonstrate the effectiveness and advantages of our SEC framework over existing SC methods and K-means-based clustering methods. Our SEC framework significantly outperforms SC using the Nyström algorithm on unseen data. Index Terms — Linearity regularization, out-of-sample clustering, spectral clustering, spectral embedded clustering

INFO2009 2012-13 Resource Group 21 - We know where you live

We know where you live is an entertaining and informative quiz show highlighting the dangers resulting from a lack of awareness of Facebook's privacy and security settings. The game show is complemented by a short tutorial explaining these settings. The show is aimed at a wider audience and is suitable for all

A multi-band centroid contrastive reconstruction fusion network for motor imagery electroencephalogram signal decoding

Motor imagery (MI) brain-computer interface (BCI) assist users in establishing direct communication between their brain and external devices by decoding the movement intention of human electroencephalogram (EEG) signals. However, cerebral cortical potentials are highly rhythmic and sub-band features, different experimental situations and subjects have different categories of semantic information in specific sample target spaces. Feature fusion can lead to more discriminative features, but simple fusion of features from different embedding spaces leading to the model global loss is not easily convergent and ignores the complementarity of features. Considering the similarity and category contribution of different sub-band features, we propose a multi-band centroid contrastive reconstruction fusion network (MB-CCRF). We obtain multi-band spatio-temporal features by frequency division, preserving the task-related rhythmic features of different EEG signals; use a multi-stream cross-layer connected convolutional network to perform a deep feature representation for each sub-band separately; propose a centroid contrastive reconstruction fusion module, which maps different sub-band and category features into the same shared embedding space by comparing with category prototypes, reconstructing the feature semantic structure to ensure that the global loss of the fused features converges more easily. Finally, we use a learning mechanism to model the similarity between channel features and use it as the weight of fused sub-band features, thus enhancing the more discriminative features, suppressing the useless features. The experimental accuracy is 79.96% in the BCI competition Ⅳ-Ⅱa dataset. Moreover, the classification effect of sub-band features of different subjects is verified by comparison tests, the category propensity of different sub-band features is verified by confusion matrix tests and the distribution in different classes of each sub-band feature and fused feature are showed by visual analysis, revealing the importance of different sub-band features for the EEG-based MI classification task

The State as both Regulator and Player: the Politics of Transfer of Development Rights in China

The conventional argument that the introduction of transfer of development rights (TDR) shifts the power of land use regulation from the state to the market is increasingly under challenge. In China, the state's grip on land is reinforced through TDR, in which the state is both regulator and player. This state‐dominated form of TDR affects China in three ways. First, competing aspirations of different scales of government complicate how TDR is implemented. Although the central state promotes TDR to maintain a national balance of arable land, some local states instrumentalize it to expand their landed basis of accumulation. Secondly, TDR tends to benefit the state but not its people. It may increase the fiscal income of the sending government and lessen the land shortage of the receiving government, but sometimes at the expense of the interests of land users without land ownership. Thirdly, given the state's deep involvement in TDR programs, the key for China's TDR to protect arable land lies not so much in clear property rights or a fully fledged market as in effective checks and balances regarding the state's powers over TDR. These three observations attest to the embeddedness of TDR in the local political economy

Effect of Er-Rich Precipitates on Microstructure and Electrochemical Behavior of the Al–5Zn–0.03In Alloy

The effect of Er-rich precipitates on microstructure and electrochemical behavior of the Al–Zn–In anode alloy is investigated. The results showed that with the increase in Er content, the microstructure was refined, the amount of interdendritic precipitates gradually increased, and the morphology changed from discontinuous to continuous network gradually. With the addition of Er element, the self-corrosion potential of the Al–5Zn–0.03In–xEr alloy moved positively, the self-corrosion current density decreased, and the corrosion resistance increased. When the Er content was less than 1 wt.%, the addition of Er improved the dissolution state of the Al–5Zn–0.03In–xEr alloy, and increased the current efficiency of the Al–5Zn–0.03In–xEr alloy. When the Er content was more than 1 wt.%, the current efficiency was reduced. The major precipitate of the alloy was Al3Er. According to the element composition of Al3Er in the Al–Zn–In–Er alloy, the simulated-segregated-phase alloy was melted to explain the effect of Al3Er segregation on the electrochemical behavior of alloys, and the polarization curve and AC impedance spectrum of the simulated-segregated-phase alloy and the Al–Zn–In alloy were measured. The results showed that Al3Er was an anodic segregation phase in the Al–Zn–In–Er alloy, and the preferential dissolution of the segregation phase would occur in the alloy, but the Al3Er phase itself was passivated in the dissolution process, which inhibited the further activation of the dissolution reaction of the Al–Zn–In–Er alloy to a certain extent