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The reinsured (original insurer) would face liability by section 13A of the Insurance Act 2015 in the UK and incur the costs or expenses of investigating and defending against the insured’s valid claims, where the reinsured withholds or delays paying insurance proceeds to the insured. The reinsurer generally would not be held liable for the unreinsured contractual liability and costs unless special requirements are met. The critical points for the reinsured to recover the reimbursement of damages and expenses from the reinsurer are to confirm the reinsurer’s actual participation or intention in refusing to indemnify the original assured timeously or in defending against the insured’s valid claims by way of proving the reinsurer’s compulsion or identifying them as a joint enterprise. The follow-the-settlements clause cannot render the reinsurer liable for the unreinsured liability. It is more reasonable that the policy limits only restrict the sums reinsured but do not cap the unreinsured damages and costs. Reinsurance, contractual liability, late payment, joint enterprise, policy limits

Multi-signatures (MS) are a special type of public-key signature (PKS) in which multiple signers participate cooperatively to generate a signature for a single message. Recently, applications that use an MS scheme to strengthen the security of blockchain wallets or to strengthen the security of blockchain consensus protocols are attracting a lot of attention. In this paper, we propose an efficient two-round MS scheme based on Okamoto signatures rather than Schnorr signatures. To this end, we first propose a new PKS scheme by modifying the Okamoto signature scheme and prove the unforgeability of our PKS scheme under the discrete logarithm assumption in the algebraic group model (AGM) and the non-programmable random oracle model (ROM). Next, we propose a two-round MS scheme based on the new PKS scheme and prove the unforgeability of our MS scheme under the discrete logarithm assumption in the AGM and the non-programmable ROM. Our MS scheme is the first one to prove security among two-round MS based on Okamoto signatures.

This survey reviews the two most prominent group-oriented anonymous signature schemes and analyzes the existing approaches for their problem: balancing anonymity against traceability. Group signatures and ring signatures are the two leading competitive signature schemes with a rich body of research. Both group and ring signatures enable user anonymity with group settings. Any group user can produce a signature while hiding his identity in a group. Although group signatures have predefined group settings, ring signatures allow users to form ad-hoc groups. Preserving user identities provided an advantage for group and ring signatures. Thus, presently many applications utilize them. However, standard group signatures enable an authority to freely revoke signers’ anonymity. Thus, the authority might weaken the anonymity of innocent users. On the other hand, traditional ring signatures maintain permanent user anonymity, allowing space for malicious user activities; thus achieving the requirements of privacy-preserved traceability in group signatures and controlled anonymity in ring signatures has become desirable. This paper reviews group and ring signatures and explores the existing approaches that address the identification of malicious user activities. We selected many papers that discuss balancing user tracing and anonymity in group and ring signatures. Since this paper scrutinizes both signatures from their basic idea to obstacles including tracing users, it provides readers a broad synthesis of information about two signature schemes with the knowledge of current approaches to balance excessive traceability in group signatures and extreme anonymity in ring signatures. This paper will also shape the future research directions of two critical signature schemes that require more awareness.

Signature identification and verification are some of the biometric systems used for personal identification. Signatures can be considered as authentication of an individual by the analysis of handwriting style, subjected to inter-personal and intra-personal variations. This paper presents an extensive systematic overview of online and offline signature identification and verification techniques. In offline signature verification, surveys related to two approaches, namely, writer-dependent, and writer-independent approaches are presented. Moreover, the compiled study of feature extraction and classification techniques used for signature identification and verification process has also been incorporated. Several databases introduced in the literature are considered to evaluate different signature identification and verification techniques and corresponding results are reported in this article. The entire survey is further summarized in the form of a table for comparisons. In order to reveal the superiority of the present survey, the comparison of the present survey with the existing recent survey works has also been presented. Finally, future directions are provided for further research.

Summary 275 I. Introduction 276 II. Ca²⁺ signalling pathways 276 III. Shaping Ca²⁺ signatures 278 IV. Ca²⁺ influx channels 278 V. Ca²⁺ influx channels as modulators of Ca²⁺ signatures 281 VI. Ca²⁺ efflux transporters 282 VII. Ca²⁺ efflux transporters as modulators of Ca²⁺ signatures 284 VIII. The shaping of noncytosolic Ca²⁺ signatures 285 IX. Future insights into the role of Ca²⁺ oscillators from modelling studies 287 X. Conclusions and perspectives 288 Acknowledgements 288 References 288 In numerous plant signal transduction pathways, Ca²⁺ is a versatile second messenger which controls the activation of many downstream actions in response to various stimuli. There is strong evidence to indicate that information encoded within these stimulus-induced Ca²⁺ oscillations can provide signalling specificity. Such Ca²⁺ signals, or 'Ca²⁺ signatures', are generated in the cytosol, and in noncytosolic locations including the nucleus and chloroplast, through the coordinated action of Ca²⁺ influx and efflux pathways. An increased understanding of the functions and regulation of these various Ca²⁺ transporters has improved our appreciation of the role these transporters play in specifically shaping the Ca²⁺ signatures. Here we review the evidence which indicates that Ca²⁺ channel, Ca²⁺-ATPase and Ca²⁺ exchanger isoforms can indeed modulate specific Ca²⁺ signatures in response to an individual signal.

Ovarian cancer (OV) is one of the leading causes of cancer deaths in women worldwide. Late diagnosis and heterogeneous treatment result to poor survival outcomes for patients with OV. Therefore, we aimed to develop novel biomarkers for prognosis prediction from the potential molecular mechanism of tumorigenesis. Eight eligible data sets related to OV in GEO database were integrated to identify differential expression genes (DEGs) between tumour tissues and normal. Enrichment analyses discovered DEGs were most significantly enriched in G2/M checkpoint signalling pathway. Subsequently, we constructed a multi‐gene signature based on the LASSO Cox regression model in the TCGA database and time‐dependent ROC curves showed good predictive accuracy for 1‐, 3‐ and 5‐year overall survival. Utility in various types of OV was validated through subgroup survival analysis. Risk scores formulated by the multi‐gene signature stratified patients into high‐risk and low‐risk, and the former inclined worse overall survival than the latter. By incorporating this signature with age and pathological tumour stage, a visual predictive nomogram was established, which was useful for clinicians to predict survival outcome of patients. Furthermore, SNRPD1 and EFNA5 were selected from the multi‐gene signature as simplified prognostic indicators. Higher EFNA5 expression or lower SNRPD1 indicated poorer outcome. The correlation between signature gene expression and clinical characteristics was observed through WGCNA. Drug‐gene interaction was used to identify 16 potentially targeted drugs for OV treatment. In conclusion, we established novel gene signatures as independent prognostic factors to stratify the risk of OV patients and facilitate the implementation of personalized therapies.

Glioblastoma (GBM) is one of the most common malignant and incurable brain tumors. The identification of a gene signature for GBM may be helpful for its diagnosis, treatment, prediction of prognosis and even the development of treatments. In this study, we used the GSE108474 database to perform GSEA and machine learning analysis, and identified a 33-gene signature of GBM by examining astrocytoma or non-GBM glioma differential gene expression. The 33 identified signature genes included the overexpressed genes COL6A2, ABCC3, COL8A1, FAM20A, ADM, CTHRC1, PDPN, IBSP, MIR210HG, GPX8, MYL9 and PDLIM4, as well as the underexpressed genes CHST9, CSDC2, ENHO, FERMT1, IGFN1, LINC00836, MGAT4C, SHANK2 and VIPR2. Protein functional analysis by CELLO2GO implied that these signature genes might be involved in regulating various aspects of biological function, including anatomical structure development, cell proliferation and adhesion, signaling transduction and many of the genes were annotated in response to stress. Of these 33 signature genes, 23 have previously been reported to be functionally correlated with GBM; the roles of the remaining 10 genes in glioma development remain unknown. Our results were the first to reveal that GBM exhibited the overexpressed GPX8 gene and underexpressed signature genes including CHST9, CSDC2, ENHO, FERMT1, IGFN1, LINC00836, MGAT4C and SHANK2, which might play crucial roles in the tumorigenesis of different gliomas.

In this study, the effects of using handheld devices on the performance of automatic signature verification systems are studied. The authors compare the discriminative power of global and local signature features between mobile devices and pen tablets, which are the prevalent acquisition device in the research literature. Individual feature discriminant ratios and feature selection techniques are used for comparison. Experiments are conducted on standard signature benchmark databases (BioSecure database) and a state-of-the-art device (Samsung Galaxy Note). Results show a decrease in the feature discriminative power and a higher verification error rate on handheld devices. It is found that one of the main causes of performance degradation on handheld devices is the absence of pen-up trajectory information (i.e. data acquired when the pen tip is not in contact with the writing surface).

The system signature is a useful tool for studying coherent systems. For a given coherent system, various methods have been proposed in the literature to compute its signature. However, when any system signature is given, the literature does not address how to construct the corresponding coherent system(s). In this article we propose an algorithm to address this research gap. This algorithm enables the validation of whether a provided probability vector qualifies as a signature. If it does, the algorithm proceeds to generate the corresponding coherent system(s). To illustrate the applicability of this algorithm, we consider all three and four-dimensional probability vectors, verify if they are signatures, and finally obtain 5 and 20 coherent systems, respectively, which coincides with the literature (Shaked and Suarez-Llorens 2003).