Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their success in versatile applications. They generate a large amount of data that can be optimized and used efficiently by advanced deep learning (ADL) techniques. The importance of such innovations from the viewpoint of supply chain management is significant in different processes such as for broadened visibility, provenance, digitalization, disintermediation, and smart contracts. This article takes the secure IoT–blockchain data of Industry 4.0 in the food sector as a research object. Using ADL techniques, we propose a hybrid model based on recurrent neural networks (RNN). Therefore, we used long short-term memory (LSTM) and gated recurrent units (GRU) as a prediction model and genetic algorithm (GA) optimization jointly to optimize the parameters of the hybrid model. We select the optimal training parameters by GA and finally cascade LSTM with GRU. We evaluated the performance of the proposed system for a different number of users. This paper aims to help supply chain practitioners to take advantage of the state-of-the-art technologies; it will also help the industry to make policies according to the predictions of ADL.

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The video created by a surveillance cameras plays a crucial role in crime prevention and examinations in smart cities. The closed-circuit television camera (CCTV) is essential for a range of public uses in a smart city; combined with Internet of Things (IoT) technologies they can turn into smart sensors that help to ensure safety and security. However, the authenticity of the camera itself raises issues of building up integrity and suitability of data. In this paper, we present a blockchain-based system to guarantee the trustworthiness of the stored recordings, allowing authorities to validate whether or not a video has been altered. It helps to discriminate fake videos from original ones and to make sure that surveillance cameras are authentic. Since the distributed ledger of the blockchain records the metadata of the CCTV video as well, it is obstructing the chance of forgery of the data. This immutable ledger diminishes the risk of copyright encroachment for law enforcement agencies and clients users by securing possession and identity.

Background— Peripartum (PP) cardiomyopathy (CM) is a rare condition of unknown etiology that occurs in late pregnancy or early postpartum. Initial evidence suggests that genetic factors may influence PPCM. This study evaluated and replicated genome-wide association of single nucleotide polymorphisms with PPCM. Methods and Results— Genome-wide single nucleotide polymorphisms in women with verified PPCM diagnosis (n=41) were compared separately with local control subjects (n=49 postmenopausal age-discordant women with parity ≥1 and no heart failure) and iControls (n=654 women ages 30 to 84 years with unknown phenotypes). A replication study of independent population samples used new cases (PPCM2, n=30) compared with new age-discordant control subjects (local2, n=124) and with younger control subjects (n=89) and obstetric control subjects (n=90). A third case set of pregnancy-associated CM cases not meeting strict PPCM definitions (n=29) was also studied. In the genome-wide association study, 1 single nucleotide polymorphism (rs258415) met genome-wide significance for PPCM versus local control subjects ( P =2.06×10 −8 ; odds ratio [OR], 5.96). This was verified versus iControls ( P =7.92×10 −19 ; OR, 8.52). In the replication study for PPCM2 cases, rs258415 (ORs are per C allele) replicated at P =0.009 versus local2 control subjects (OR, 2.26). This replication was verified for PPCM2 versus younger control subjects ( P =0.029; OR, 2.15) and versus obstetric control subjects ( P =0.013; OR, 2.44). In pregnancy-associated cardiomyopathy cases, rs258415 had a similar effect versus local2 control subjects ( P =0.06; OR, 1.79), younger control subjects ( P =0.14; OR, 1.65), and obstetric control subjects ( P =0.038; OR, 1.99). Conclusions— Genome-wide association with PPCM was discovered and replicated for rs258415 at chromosome 12p11.22 near PTHLH . This study indicates a role of genetic factors in PPCM and provides a new locus for further pathophysiological and clinical investigation.