Multi-strategy modified sparrow search algorithm for hyperparameter optimization in arbitrage prediction models.

Deep learning models struggle to effectively capture data features and make accurate predictions because of the strong non-linear characteristics of arbitrage data. Therefore, to fully exploit the model performance, researchers have focused on network structure and hyperparameter selection using various swarm intelligence algorithms for optimization. Sparrow Search Algorithm (SSA), a classic heuristic method that simulates the sparrows' foraging and anti-predatory behavior, has demonstrated excellent performance in various optimization problems. Hence, in this study, the Multi-Strategy Modified Sparrow Search Algorithm (MSMSSA) is applied to the Long Short-Term Memory (LSTM) network to construct an arbitrage spread prediction model (MSMSSA-LSTM). In the modified algorithm, the good point set theory, the proportion-adaptive strategy, and the improved location update method are introduced to further enhance the spatial exploration capability of the sparrow. The proposed model was evaluated using the real spread data of rebar and hot coil futures in the Chinese futures market. The obtained results showed that the mean absolute percentage error, root mean square error, and mean absolute error of the proposed model had decreased by a maximum of 58.5%, 65.2%, and 67.6% compared to several classical models. The model has high accuracy in predicting arbitrage spreads, which can provide some reference for investors.

Mapping the field: A bibliometric literature review on technology mining.

Technology mining (or tech mining, TM) is an emerging research field in science, technology, and innovation studies. However, due to the rapid increase and widespread application of TM research, accurately capturing research topics and emerging developments in TM has become a challenge for scholars. Therefore, this bibliometric literature review combines quantitative methods and content analysis to explore the research foundation and development frontiers of TM and distinguish emerging research topics from relatively mature ones, aiming to deepen the understanding. More specifically, it utilizes co-citation analysis and bibliographic coupling techniques to analyze the TM publication dataset. The results indicate that TM research is mainly based on four foundational areas, and there are five current frontier clusters. Emerging topic detection further shows that technology topic analysis, technology opportunity analysis, and technology management and decision support are currently emerging TM research topics.

Prevalence and associations of sarcopenia, obesity and sarcopenic obesity in end-stage knee osteoarthritis patients.

OBJECTIVE: To identify the prevalence of obesity, sarcopenia, sarcopenic obesity in end-stage knee osteoarthritis (KOA) patients and analyze influences of obesity and sarcopenia in the progression of KOA. METHODS: A cross-sectional study was carried out among end-stage KOA patients who consecutively admitted to Orthopedic Department for TKA. We suppose that the level of decreased physical activities would be influenced by unilateral or bilateral KOA. Patient information, albumin, hemoglobin, pace, step frequency, number of comorbid conditions were collected. Bioelectrical impedance analyzer was used to analyze body composition. Obesity, sarcopenia, sarcopenic obesity rate were analyzed with accepted diagnosis criteria. Correlations between body mass index (BMI) or age and fat mass (FM), appendicular skeletal muscle mass (ASM) were analyzed. RESULTS: 138 patients (male 30, female 108) in southwest of China including 67 patients with unilateral KOA and 71 patients with bilateral KOA were analyzed. No statistic difference was found in mean albumin, prealbumin and hematocrystallin, body composition values and number of comorbid conditions. We found that BMI was positively correlated with FM (Male: R2 = 0.7177, p < 0.0001, Female: R2 = 0.8898, p < 0.0001), ASM (Male: R2 = 0.2640, p = 0.0037, Female: R2 = 0.2102, p < 0.0001), FM index (FMI) (Male: R2 = 0.6778, p < 0.0001, Female: R2 = 0.8801, p < 0.0001), and ASM index (ASMI) (Male: R2 = 0.3600, p = 0.0005, Female: R2 = 0.4208, p < 0.0001) in end-stage KOA patients. However, age was not obviously correlated with FM or FMI (Male: FM, R2 = 0.006911, p = 0.3924; FMI, R2 = 0.7554, p = 0.0009196; Female: FM, R2 = 0.001548, p = 0.8412; FMI, R2 = 0.002776, p = 0.7822). And slightly negatively correlated with ASM (Male: R2 = 0.05613, p = 0.0136, Female: R2 = 0.01327, p = 0.5433) and ASMI (Male: R2 = 0.02982, p = 0.3615; Female: R2 = 0.03696, p = 0.0462). The prevalence of obesity, sarcopenia and obesity sarcopenia differs according to different diagnosis criteria. No difference in the occurrence rate of obesity was found between bilateral KOA and unilateral KOA patients, and occurrence rates of sarcopenia and sarcopenic obesity were statistically higher in bilateral KOA than that in unilateral KOA patients. CONCLUSIONS: Obesity, sarcopenia and sarcopenic obesity are highly prevalent in end-stage KOA patients, sarcopenic obesity are more prevalent in bilateral KOA patients than that in unilateral KOA patients.

A Novel Edge Cache-Based Private Set Intersection Protocol via Lightweight Oblivious PRF.

With the rapid development of edge computing and the Internet of Things, the problem of information resource sharing can be effectively solved through multi-party collaboration, but the risk of data leakage is also increasing. To address the above issues, we propose an efficient multi-party private set intersection (MPSI) protocol via a multi-point oblivious pseudorandom function (OPRF). Then, we apply it to work on a specific commercial application: edge caching. The proposed MPSI uses oblivious transfer (OT) together with a probe-and-XOR of strings (PaXoS) as the main building blocks. It not only provides one-sided malicious security, but also achieves a better balance between communication and computational overhead. From the communication pattern perspective, the client only needs to perform OT with the leader and send a data structure PaXoS to the designated party, making the protocol extremely efficient. Moreover, in the setting of edge caching, many parties hold a set of items containing an identity and its associated value. All parties can identify a set of the most frequently accessed common items without revealing the underlying data.

Development and validation of a novel necroptosis-related gene signature for predicting prognosis and therapeutic response in Ewing sarcoma.

Ewing sarcoma (ES) is the second most common malignant bone tumor in children and has a poor prognosis due to early metastasis and easy recurrence. Necroptosis is a newly discovered cell death method, and its critical role in tumor immunity and therapy has attracted widespread attention. Thus, the emergence of necroptosis may provide bright prospects for the treatment of ES and deserves our further study. Here, based on the random forest algorithm, we identified 6 key necroptosis-related genes (NRGs) and used them to construct an NRG signature with excellent predictive performance. Subsequent analysis showed that NRGs were closely associated with ES tumor immunity, and the signature was also good at predicting immunotherapy and chemotherapy response. Next, a comprehensive analysis of key genes showed that RIPK1, JAK1, and CHMP7 were potential therapeutic targets. The Cancer Dependency Map (DepMap) results showed that CHMP7 is associated with ES cell growth, and the Gene Set Cancer Analysis (GSCALite) results revealed that the JAK1 mutation frequency was the highest. The expression of 3 genes was all negatively correlated with methylation and positively with copy number variation (CNV). Finally, an accurate nomogram was constructed with this signature and clinical traits. In short, this study constructed an accurate prognostic signature and identified 3 novel therapeutic targets against ES.

Phenotypic quantification of root spatial distribution along circumferential direction for field paddy-wheat.

Plant roots are essential for water and nutrient absorption, anchoring, mechanical support, metabolite storage and interaction with the surrounding soil environment. A comprehensive understanding of root traits provides an opportunity to build ideal roots architectural system that provides improved stability and yield advantage in adverse target environments caused by soil quality degradation, climate change, etc. However, we hypothesize that quantitative indicators characterizing root system are still need to be supplemented. Features describing root growth and distribution, until now, belong mostly to 2D indicators or reflect changes in the root system with a depth of soil layers but are rarely considered in a spatial region along the circumferential direction. We proposed five new indicators to quantify the dynamics of the root system architecture (RSA) along its eight-part circumferential orientations with visualization technology which consists of in-situ field root samplings, RSA digitization, and reconstruction according to previous research based on field experiments that conducted on paddy-wheat cultivation land with three fertilization rates. The experimental results showed that the growth space of paddy-wheat root is mainly restricted to a cylinder with a diameter of 180 mm and height of 200 mm at the seedlings stage. There were slow fluctuating trends in growth by the mean values of five new indicators within a single volume of soil. The fluctuation of five new indicators was indicated in each sampling time, which decreased gradually with time. Furthermore, treatment of N70 and N130 could similarly impact root spatial heterogeneity. Therefore, we concluded that the five new indicators could quantify the spatial dynamics of the root system of paddy-wheat at the seedling stage of cultivation. It is of great significance to the comprehensive quantification of crop roots in targeted breeding programs and the methods innovation of field crop root research.

Attribute-Based Verifiable Conditional Proxy Re-Encryption Scheme.

There are mostly semi-honest agents in cloud computing, so agents may perform unreliable calculations during the actual execution process. In this paper, an attribute-based verifiable conditional proxy re-encryption (AB-VCPRE) scheme using a homomorphic signature is proposed to solve the problem that the current attribute-based conditional proxy re-encryption (AB-CPRE) algorithm cannot detect the illegal behavior of the agent. The scheme implements robustness, that is the re-encryption ciphertext, can be verified by the verification server, showing that the received ciphertext is correctly converted by the agent from the original ciphertext, thus, meaning that illegal activities of agents can be effectively detected. In addition, the article demonstrates the reliability of the constructed AB-VCPRE scheme validation in the standard model, and proves that the scheme satisfies CPA security in the selective security model based on the learning with errors (LWE) assumption.

Efficient Lattice-Based Ring Signature Scheme without Trapdoors for Machine Learning.

Machine learning (ML) and privacy protection are inseparable. On the one hand, ML can be the target of privacy protection; on the other hand, it can also be used as an attack tool for privacy protection. Ring signature (RS) is an effective way for privacy protection in cryptography. In particular, lattice-based RS can still protect the privacy of users even in the presence of quantum computers. However, most current lattice-based RS schemes are based on a strong trapdoor like hash-and-sign, and in such constructions, there is a hidden algebraic structure, that is, added to lattice so that the trapdoor shape is not leaked, which greatly affects the computational efficiency of RS. In this study, utilizing Lyubashevsky collision-resistant hash function over lattice, we construct an RS scheme without trapdoors based on ideal lattice via Fiat‒Shamir with aborts (FSwA) protocol. Regarding security, the proposed scheme satisfies unconditional anonymity against chosen setting attacks (UA-CSA), which is stronger than anonymity against full key exposure (anonymity-FKE), and moreover, our scheme satisfies unforgeability with respect to insider corruption (EU-IC). Regarding computational overhead, compared with other RS schemes that satisfy the same degree of security, our scheme has the highest computational efficiency, the signing and verification time costs of the proposed scheme are obviously better than those of other lattice-based RS schemes without trapdoors, which is more suitable for ML scenarios.

Prevalence and associated factors of dry skin among older inpatients in hospitals and nursing homes: A multicenter cross-sectional study.

BACKGROUND/OBJECTIVES: Dry skin is a common skin problem in older persons. Aim of this study was to determine the prevalence, associated factors of dry skin in older inpatients. DESIGN: A multicenter cross-sectional study was designed and conducted. SETTINGS/PARTICIPANTS: On 31 March and 29 May in 2021 two days, fifty hospitals and two nursing homes in China participated in the study. In total, 33,769 participants were included. The mean age was 73.2 (SD 8.9) years. METHODS: A whole-body skin examination and associated data collection were performed by 1067 trained nurses based on a standardized data form and methods. Descriptive and univariable analyses and multivariable logistic regressions were conducted. RESULTS: In total, 11,602 participants had dry skin with a prevalence of 34.4%, mainly located on the upper and lower limbs with very severe skin dryness, 21.2% of the participants reported that their dry skin had pruritus, and 12.5% complained that sleep was affected by dry skin. The stronger predictor for dry skin was nursing homes (OR 5.07, 95% CI 3.99-6.45). Other predictors for dry skin were age, male sex, nutrition, lower activity level, skincare dependence, renal and pulmonary impairment, diabetes mellitus, varicose veins, cardiovascular diseases and Parkinsonism, diuretics, statins and antibiotics. The predictive model of area under ROC curve was 0.628(95% CI 0.622-0.634). CONCLUSIONS: The prevalence of dry skin among Chinese older patients was at high level and was associated with multiple factors. Persons with skin dryness have a higher proportion of skin itching and poor sleep. REGISTRATION: It has been registered in the Chinese Clinical Trial Registry (ChiCTR2100042893).

Redactable Blockchain Trust Scheme Based on Reputation Consensus for MEC.

Blockchain technology can build trust, reduce costs, and accelerate transactions in the mobile edge computing (MEC) and manage computing resources using the smart contract. However, the immutability of blockchain also poses challenges for the MEC, such as the smart contract with bugs cannot be modified or deleted. We propose a redactable blockchain trust scheme based on reputation consensus and a one-way trapdoor function in response to the problem that data on the blockchain, which is an error or invalid needs to be modified or deleted. The scheme calculates each user's reputation based on their currency age and behavior. The SM2 asymmetric cryptography algorithm is used as the one-way trapdoor function to construct a new Merkle tree structure, which guarantees the legitimacy of the modification or deletion after verification and vote. The simulation experiments show that the modification or deletion does not change the existing blockchain structure and the links of blocks. Furthermore, the consensus verification accurately passes after the modification or deletion operations, which indicates the proposed scheme is feasible.

The Prevalence, Characteristics, and Prevention Status of Skin Injury Caused by Personal Protective Equipment Among Medical Staff in Fighting COVID-19: A Multicenter, Cross-Sectional Study.

Objective: To investigate the prevalence, characteristics, and preventive status of skin injuries caused by personal protective equipment (PPE) in medical staff. Approach: A cross-sectional survey was conducted online for understanding skin injuries among medical staff fighting COVID-19 in February 8-22, 2020. Participants voluntarily answered and submitted the questionnaire with cell phone. The questionnaire items included demographic data, grade of PPE and daily wearing time, skin injury types, anatomical sites, and preventive measures. Univariable analyses and logistic regression analyses were used to explore the risk factors associated with skin injuries. Results: A total of 4,308 respondents were collected from 161 hospitals and 4,306 respondents were valid. The overall prevalence of skin injuries was 42.8% (95% confidence interval [CI] 41.30-44.30) with three types of device-related pressure injuries, moist-associated skin damage, and skin tear. Co-skin injuries and multiple location injuries were 27.4% and 76.8%, respectively. The logistic regression analysis indicated that sweating (95% CI for odds ratio [OR] 87.52-163.11), daily wearing time (95% CI for OR 1.61-3.21), male (95% CI for OR 1.11-2.13), and grade 3 PPE (95% CI for OR 1.08-2.01) were associated with skin injuries. Only 17.7% of respondents took prevention and 45.0% of skin injuries were treated. Innovation: This is the first cross-sectional survey to understand skin injuries in medical staff caused by PPE, which is expected to be a benchmark. Conclusion: The skin injuries among medical staff are serious, with insufficient prevention and treatment. A comprehensive program should be taken in the future.

Secure two-party computation of solid triangle area and tetrahedral volume based on cloud platform.

With the emergence and widespread application of cloud computing, the use of cloud platforms to solve the problem of secure multi-party computation has emerged as a new research direction. The traditional computation of a solid geometry is performed through mutual interactions between two parties, which is not suitable in an untrusted cloud computing environment. In this paper, we first design a basic protocol for a secure Euclidean distance calculation that is suitable for cloud platforms and can serve as a building block for other protocols on cloud platforms. Using the solution of the Euclidean distance problem as such a building block, we provide a new method that converts the problems of calculating solid triangular areas and solid tetrahedral volumes into the calculation of distances and determinants in three-dimensional space. Then, we discuss solid point-line distance calculations, which extent the idea of the spatial geometry security problem. We present protocols for the above problems and prove that the proposed protocols can resist conspiracy among users and the untrusted cloud platform so that they can effectively ensure the privacy of the users. We also analyze the performances of these solutions. The analysis results show that our scheme is more versatile.

A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network.

This study investigates the randomness detection of cryptographic algorithms in network security. To effectively test and verify the security of ZigBee protocol in the Internet of Things, the study combines with the characteristics of ZigBee networks, and it rationally organizes and divides test modes based on the binary matrix rank theory test. Then this paper proposes a randomness detection method of ZigBee protocol in a wireless sensor network. The proposed method solves the one-sidedness that the binary matrix rank test simply assesses random sequences by linear correlation. The proposed assessment method can effectively appraise whether the ZigBee protocol has an encryption mechanism and encryption strength. Simulation results show that this method has the characteristics of fewer errors and high reliability.

Weighted norm inequalities for Toeplitz type operators associated to generalized Calderón-Zygmund operators.

Let [Formula: see text] be a generalized Calderón-Zygmund operator or [Formula: see text] ( the identity operator), let [Formula: see text] and [Formula: see text] be the linear operators, and let [Formula: see text]. Denote the Toeplitz type operator by [Formula: see text]where [Formula: see text] and [Formula: see text] is fractional integral operator. In this paper, we establish the sharp maximal function estimates for [Formula: see text] when b belongs to weighted Lipschitz function space, and the weighted norm inequalities of [Formula: see text] on weighted Lebesgue space are obtained.

[Biomechanical evaluation of three-dimensional stability of anterior approach screw fixation through C2 vertebral body to C1 lateral mass].

OBJECTIVE: To determine the three-dimensional stability of C1-C2 after anterior approach screw fixation through C2 vertebral body to C1 lateral mass for C1-C2 instability or dislocation. METHODS: The three-dimensional range of motion of atlantoaxial joint were measured in 16 human cadaveric specimens under four conditions: the intact state (1st group), odontoid fracture of type II (2nd group), instrumentation with posterior C1-C2 trans-articular screw fixation (Magerl technique) (3rd group) and anterior approach screw fixation through C2 vertebral body to C1 lateral mass (4th group) respectively. RESULTS: There was generally significant difference between 1st group and other groups and between 2nd group and other groups by statistics analysis (P < 0.001). Range of motion significantly decreased in 3rd group and 4th group in all directions. There was generally no significant difference between the two methods by statistical analysis (P > 0.05). CONCLUSION: Anterior approach screw fixation through C2 vertebral body to C lateral mass provides satisfied stability. It provides the equivalent effect to Magerl technique. It is a kind of reliable surgery choice for the treatment of instability or dislocation of C1-C2 joint.