Lockdown is an effective nonpharmaceutical intervention to reduce coronavirus disease 2019 (COVID-19) transmission, but it restricts daily activity. We aimed to investigate the impact of lockdown on ...pediatric body weight and body mass index (BMI).
The systematic review and meta-analysis were conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement. Four online databases (EMBASE, Medline, the Cochrane Library and CINAHL) were searched.
The pooled results showed that lockdown was associated with significant body weight gain (MD 2.67, 95% CI 2.12-3.23;
< 0.00001). The BMI of children with comorbidities or obesity did not change significantly. The BMI of general population was significantly higher during lockdown than before the pandemic (MD 0.94, 95% CI 0.32-1.56;
= 0.003). However, heterogeneity was high (I
= 84%). Among changes in weight classification, increases in the rates of obesity (OR 1.23, 95% CI 1.10-1.37;
= 0.0002) and overweight (OR 1.17, 95% CI 1.06-1.29;
= 0.001) were reported.
Our meta-analysis showed significant increases in body weight and BMI during lockdown among school-age children and adolescents. The prevalence of obesity and overweight also increased. The COVID-19 pandemic worsened the burden of childhood obesity.
In 2014, Turkanovic et al. proposed a smart card-based authentication scheme for heterogeneous ad hoc wireless sensor network. This scheme is very efficient since it employs only hash function and ...XOR operation. However, we found that Turkanovic et al.'s scheme is vulnerable to impersonation attack with node capture, stolen smart card attack, sensor node spoofing attack, stolen verifier attack, and fails to ensure backward secrecy. We propose an efficient scheme to overcome all those weaknesses. Moreover, we also propose an advanced scheme, which provides perfect forward secrecy without much modification from the first proposed scheme.
•Introduce contextual information into the VQA task for the first time and propose a context-aware model CAAN.•Employ the positional relationship information between the image regions and the image ...to obtain a context-enhanced visual representation.•First introduce question contextual information to enhance the question feature representation in VQA.•Reach a significant performance improvement or comparable performance compared with some other state-of-the-art VQA models.
Understanding multimodal information is the key to visual question answering (VQA) tasks. Most existing approaches use attention mechanisms to acquire fine-grained information understanding. However, these approaches with merely attention mechanisms do not solve the potential understanding bias problem. Hence, this paper introduces contextual information into VQA for the first time and presents a context-aware attention network (CAAN) to tackle the case. By improving the modular co-attention network (MCAN) framework, CAAN’s main work includes: designing a novel absolute position calculation method based on the coordinates of each image region in the image and the image’s actual size, the position information of all image regions are integrated as contextual information to enhance the visual representation; based on the question itself, several internal contextual information representations are introduced to participate in the modeling of the question words, solving the understanding bias caused by the similarity of the question. Additionally, we also designed two models of different scales, namely CAAN-base and CAAN-large, to explore the effect of the field of view on interaction. Finally, extensive experimental results show that CAAN significantly outperforms MCAN and achieves comparable or even better performance than other state-of-the-art approaches, proving our method can tackle the understanding bias.
Data leakage in electronic health records (EHRs) could result in the compromise of patient privacy (e.g. medical conditions). Generally most data in EHRs remain unchanged once they are uploaded to ...the system; thus, blockchain can be potentially used to facilitate the sharing of such data. Different participating medical organizations and individuals (e.g. medical practitioners, hospitals, medical labs and insurance companies) can then access EHRs stored on the blockchain with a higher level of confidence. In this paper, a blockchain based searchable encryption scheme for EHRs is proposed. The index for EHRs is constructed through complex logic expressions and stored in the blockchain, so that a data user can utilize the expressions to search the index. As only the index is migrated to the blockchain to facilitate propagation, the data owners have full control over who can see their EHRs data. The use of blockchain technology ensures the integrity, anti-tampering, and traceability of EHRs’ index. Finally, the performance of the proposed scheme is evaluated from two aspects, namely in terms of the overhead for extracting the document IDs from EHRs and the overhead associated with conducting transactions on smart contract in Ethereum.
•Blockchain based searchable encryption for electronic health record sharing.•File encryption, index construction, transaction generation and searching.•Designated smart contract in blockchain to facilitate monetary rewarding.
•A high-capacity separable reversible data hiding scheme is proposed.•A joint lossless compression scheme is proposed to reserve embedding room.•Image recovery and secret data extraction are ...error-free.•The visual quality of the decrypted images is high.
In this paper, we propose a novel reversible data hiding method in encrypted images. The proposed method takes full advantage of the spatial correlation in the original images to vacate room for embedding data before image encryption. By jointly using an extended run-length coding and a block-based most significant bit (MSB) plane rearrangement mechanism, the MSB planes of images can be compressed efficiently to generate room for high-capacity embedding. The receiver can extract data directly from encrypted images with only the data hiding key, and the original image or the high-quality plain image that contains secret data can be recovered with only the encryption key. The experimental results prove that the proposed method can reach a high embedding rate and a high PSNR.
Cloud storage is an increasingly popular application of cloud computing, which can provide on-demand outsourcing data services for both organizations and individuals. However, users may not fully ...trust the cloud service providers (CSPs) in that it is difficult to determine whether the CSPs meet their legal expectations for data security. Therefore, it is critical to develop efficient auditing techniques to strengthen data owners' trust and confidence in cloud storage. In this paper, we present a novel public auditing scheme for secure cloud storage based on dynamic hash table (DHT), which is a new two-dimensional data structure located at a third parity auditor (TPA) to record the data property information for dynamic auditing. Differing from the existing works, the proposed scheme migrates the authorized information from the CSP to the TPA, and thereby significantly reduces the computational cost and communication overhead. Meanwhile, exploiting the structural advantages of the DHT, our scheme can also achieve higher updating efficiency than the state-of-the-art schemes. In addition, we extend our scheme to support privacy preservation by combining the homomorphic authenticator based on the public key with the random masking generated by the TPA, and achieve batch auditing by employing the aggregate BLS signature technique. We formally prove the security of the proposed scheme, and evaluate the auditing performance by detailed experiments and comparisons with the existing ones. The results demonstrate that the proposed scheme can effectively achieve secure auditing for cloud storage, and outperforms the previous schemes in computation complexity, storage costs and communication overhead.
Visual Question Answering (VQA) is a learning task that combines computer vision with natural language processing. In VQA, it is important to understand the alignment between visual concepts and ...linguistic semantics. In this paper, we proposed a Pre-training Model Based on Parallel Cross-Modality Fusion Layer (P-PCFL) to learn the fine-grained relationship between vision and language. The P-PCFL model is composed of three Encoders: Object Encoder, Language Encoder, and Parallel Cross-Modality Fusion Encoder, with Transformer as the core. We use four different Pre-training missions, namely, Cross-Modality Mask Language Modeling, Cross-Modality Mask Region Modeling, Image-Text Matching, and Image-Text Q&A, to pre-train the P-PCFL model and improve its reasoning and universality, which help to learn the relationship between Intra-modality and Inter-modality. Experimental results on the platform of Visual Question Answering dataset VQA v2.0 show that the Pre-trained P-PCFL model has a good effect after fine-tuning the parameters. In addition, we also conduct ablation experiments and provide some results of Attention visualization to verify the effectiveness of P-PCFL model.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A high prevalence rate of macrolide-resistant Mycoplasma pneumoniae (MRMP) has been reported in Asia. We performed a systematic review and meta-analysis to investigate the effect of macrolide ...resistance on the manifestations and clinical judgment during M. pneumoniae infections. We found no difference in clinical severity between MRMP and macrolide-sensitive Mycoplasma pneumoniae (MSMP) infections. However, in the pooled data, patients infected with MRMP had a longer febrile period (1.71 days), length of hospital stay (1.61 day), antibiotic drug courses (2.93 days), and defervescence time after macrolide treatment (2.04 days) compared with patients infected with MSMP. The risk of fever lasting for >48 hours after macrolide treatment was also significantly increased (OR 21.24), and an increased proportion of patients was changed to second-line treatment (OR 4.42). Our findings indicate diagnostic and therapeutic challenges after the emergence of MRMP. More precise diagnostic tools and clearly defined treatment should be appraised in the future.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, ODKLJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Secret sharing is a useful method which divides a secret message into several shares for security. During the recovery procedure, only when sufficient shares are obtained, the secret message can be ...recovered. This paper proposes two novel reversible data hiding schemes in encrypted image via secret sharing over Galois fields <inline-formula> <tex-math notation="LaTeX">{{GF}}{({p})} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">{{GF}}{(}{{2}^{{8}}}{)} </tex-math></inline-formula>. The content owner first applies a specific encryption method through block and pixel permutation and Shamir's secret sharing. Then, the theoretical demonstration is introduced to explain that the generated shares are suitable for data embedding over <inline-formula> <tex-math notation="LaTeX">{{GF}}{({p})} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">{{GF}}{(}{{2}^{{8}}}{)} </tex-math></inline-formula>. Finally, two embedding algorithms over <inline-formula> <tex-math notation="LaTeX">{{GF}}{({p})} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">{{GF}}{(}{{2}^{{8}}}{)} </tex-math></inline-formula> are presented, and on the receiver side, with different keys, additional data can be extracted correctly and original image can be recovered losslessly. Experimental results show that our schemes can achieve better rate-distortion performance than some state-of-the-art schemes.
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