A Blind Batch Encryption and Public Ledger-Based Protocol for Sharing Sensitive Data

For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be preserved.Data owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the requester.We prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file keepers.We also provide security analysis in the context of four typical attacks.

Countermeasure against blinding attack for single-photon detectors in quantum key distribution

Quantum key distribution(QKD),rooted in quantum mechanics,offers information-theoretic security.However,practi-cal systems open security threats due to imperfections,notably bright-light blinding attacks targeting single-photon detectors.Here,we propose a concise,robust defense strategy for protecting single-photon detectors in QKD systems against blinding attacks.Our strategy uses a dual approach:detecting the bias current of the avalanche photodiode(APD)to defend against con-tinuous-wave blinding attacks,and monitoring the avalanche amplitude to protect against pulsed blinding attacks.By integrat-ing these two branches,the proposed solution effectively identifies and mitigates a wide range of bright light injection attempts,significantly enhancing the resilience of QKD systems against various bright-light blinding attacks.This method forti-fies the safeguards of quantum communications and offers a crucial contribution to the field of quantum information security.

Treatment of uveitis and scleritis patients in Malaysia

●AIM:To determine the common causes and visual outcome after treatment among uveitis and scleritis patients.●METHODS:This is a retrospective cohort observational study.All consecutive clinical records of patients with newly diagnosed uveitis and scleritis over a 4-year period,from Jan.1,2017 to Dec.31,2020,were analysed.Data was collected at the presentation and included a follow-up period of one year.●RESULTS:A total of 288 patients were recruited during the study period.Anterior uveitis was the most common anatomical diagnosis(50.0%)followed by panuveitis(25.0%),scleritis(13.5%),posterior uveitis(6.9%),and intermediate uveitis(4.5%).Viral Herpes was the most common cause of infectious cases,while Vogt-Koyanagi-Harada(VKH)disease and human leucocyte antigen(HLA)B27 spondyloarthropathy were the leading causes of identifiable non-infectious cases.Majority of patients presented with unilateral,non-granulomatous uveitis with an absence of hypopyon.Anatomical locations like posterior uveitis and panuveitis,and visual acuity worse than 3/60 at presentation were the factors associated with poor visual outcomes(P<0.05).About 60%of patients had an identifiable cause for the uveitis and scleritis,with nearly equal distribution of infectious(n=85,29.5%)and noninfectious causes(n=84,29.2%).About 14.5%of patients were clinically blind at 1y of follow-up.The most common complication in our uveitis patients was glaucoma(47.5%),followed by cystoid macula oedema(18.9%)and cataract(13.9%).●CONCLUSION:Uveitis and scleritis are important causes of ocular morbidity.They are potentially blinding diseases which can have a good outcome if diagnosed and treated early.

Comparison between local-made and imported porous polyethylene orbital implant:a randomized controlled equivalence trial and multicenter study

AIM:To compare the exposure rate,infection rate,percentage of enhancement,and success rate between Medpor and the three-dimensional printed polyethylene(3DP-PE)orbital implant in a preliminary report.METHODS:This prospective,randomized,equivalence,controlled trial was conducted at two institutes.The equivalent margin was±10%.The sample size for the equivalence trial was 174 participants per group.Patients who were eligible for enucleations received either Medpor or 3DP-PE implants based on a randomized block of six.The surgeries were performed by five oculoplastic surgeons.The assessor and patients were masked.The magnetic resonance imaging(MRI)of the orbit was performed at least 6mo after operation and the fibrovascular ingrowth was analyzed using the Image J software.Follow-up continued at least 1y after surgery.The intention to treat and per protocol approaches were used.RESULTS:Totally 128 patients met the criteria in the report.Fifty Medpor and 553DP-PE cases completed the trial.The most common cause of blindness was trauma.The mean follow-up times of Medpor and 3DP-PE were 33 and 40mo respectively.The exposure rate was not statistically significant between two groups(6.0%and 7.3%),P<0.05,95%CI(-9.8%,+12.0%).The success rates were 94%(Medpor)and 92.7%(3DP-PE).No postoperative infection was reported.Nine patients had MRI tests and two had implant exposures with 66.3% enhancement at 75mo(Medpor)and 58% enhancement at 57mo(3DP-PE)postoperatively.CONCLUSION:There is no statistically significant difference in exposure rate and success rate between Medpor and 3DP-PE in enucleation in the report.However,we cannot conclude that they are equivalent in terms of the exposure rate and success rate because the 95%CI is wider than±10%.The infection rate is equivalent in both groups.

A quantum blind signature scheme based on dense coding for non-entangled states

In some schemes, quantum blind signatures require the use of difficult-to-prepare multiparticle entangled states. By considering the communication overhead, quantum operation complexity, verification efficiency and other relevant factors in practical situations, this article proposes a non-entangled quantum blind signature scheme based on dense encoding. The information owner utilizes dense encoding and hash functions to blind the information while reducing the use of quantum resources. After receiving particles, the signer encrypts the message using a one-way function and performs a Hadamard gate operation on the selected single photon to generate the signature. Then the verifier performs a Hadamard gate inverse operation on the signature and combines it with the encoding rules to restore the message and complete the verification.Compared with some typical quantum blind signature protocols, this protocol has strong blindness in privacy protection,and higher flexibility in scalability and application. The signer can adjust the signature operation according to the actual situation, which greatly simplifies the complexity of the signature. By simultaneously utilizing the secondary distribution and rearrangement of non-entangled quantum states, a non-entangled quantum state representation of three bits of classical information is achieved, reducing the use of a large amount of quantum resources and lowering implementation costs. This improves both signature verification efficiency and communication efficiency while, at the same time, this scheme meets the requirements of unforgeability, non-repudiation, and prevention of information leakage.

Blind Recognition of Non-Binary LDPC Codes Based on Ant Colony Optimization

This paper introduces a novel blind recognition of non-binary low-density parity-check(LDPC)codes without a candidate set,using ant colony optimization(ACO)algorithm over additive white Gaussian noise(AWGN)channels.Specifically,the scheme that effectively combines the ACO algorithm and the non-binary elements over finite fields is proposed.Furthermore,an improved,simplified elitist ACO algorithm based on soft decision reliability is introduced to recognize the parity-check matrix over noisy channels.Simulation results show that the recognition rate continuously increases with an increased signalto-noise ratio(SNR)over the AWGN channel.

The gut-eye axis:from brain neurodegenerative diseases to age-related macular degeneration

Age-related macular degeneration is a serious neurodegenerative disease of the retina that significantly impacts vision.Unfortunately,the specific pathogenesis remains unclear,and effective early treatment options are consequently lacking.The microbiome is defined as a large ecosystem of microorganisms living within and coexisting with a host.The intestinal microbiome undergoes dynamic changes owing to age,diet,genetics,and other factors.Such dysregulation of the intestinal flora can disrupt the microecological balance,resulting in immunological and metabolic dysfunction in the host,and affecting the development of many diseases.In recent decades,significant evidence has indicated that the intestinal flora also influences systems outside of the digestive tract,including the brain.Indeed,several studies have demonstrated the critical role of the gut-brain axis in the development of brain neurodegenerative diseases,including Alzheimer’s disease and Parkinson’s disease.Similarly,the role of the“gut-eye axis”has been confirmed to play a role in the pathogenesis of many ocular disorders.Moreover,age-related macular degeneration and many brain neurodegenerative diseases have been shown to share several risk factors and to exhibit comparable etiologies.As such,the intestinal flora may play an important role in age-related macular degeneration.Given the above context,the present review aims to clarify the gut-brain and gut-eye connections,assess the effect of intestinal flora and metabolites on age-related macular degeneration,and identify potential diagnostic markers and therapeutic strategies.Currently,direct research on the role of intestinal flora in age-related macular degeneration is still relatively limited,while studies focusing solely on intestinal flora are insufficient to fully elucidate its functional role in age-related macular degeneration.Organ-on-a-chip technology has shown promise in clarifying the gut-eye interactions,while integrating analysis of the intestinal flora with research on metabolites through metabolomics and other techniques is crucial for understanding their potential mechanisms.

Quantum circuit-based proxy blind signatures:A novel approach and experimental evaluation on the IBM quantum cloud platform

This paper presents a novel approach to proxy blind signatures in the realm of quantum circuits,aiming to enhance security while safeguarding sensitive information.The main objective of this research is to introduce a quantum proxy blind signature(QPBS)protocol that utilizes quantum logical gates and quantum measurement techniques.The QPBS protocol is constructed by the initial phase,proximal blinding message phase,remote authorization and signature phase,remote validation,and de-blinding phase.This innovative design ensures a secure mechanism for signing documents without revealing the content to the proxy signer,providing practical security authentication in a quantum environment under the assumption that the CNOT gates are securely implemented.Unlike existing approaches,our proposed QPBS protocol eliminates the need for quantum entanglement preparation,thus simplifying the implementation process.To assess the effectiveness and robustness of the QPBS protocol,we conduct comprehensive simulation studies in both ideal and noisy quantum environments on the IBM quantum cloud platform.The results demonstrate the superior performance of the QPBS algorithm,highlighting its resilience against repudiation and forgeability,which are key security concerns in the realm of proxy blind signatures.Furthermore,we have established authentic security thresholds(82.102%)in the presence of real noise,thereby emphasizing the practicality of our proposed solution.

For LEO Satellite Networks: Intelligent Interference Sensing and Signal Reconstruction Based on Blind Separation Technology

In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.

Ophthalmic complications of injectable facial fillers

The recently published mini-review article by Miotti et al is an effort to clarify various aspects regarding the choice between fat grafts and fillers in facial aesthetic surgery.One of the complications associated with the administration of fillers is the possibility of vascular injury and spread of the dermal filler into the orbit,causing unexpected effects at a site distant from that of the initial injection,including ophthalmoplegia,ptosis and even visual compromise.Acute vision loss following filler injection is a devastating complication,occurring in up to 0.0008%of cases.The greatest risk of this complication occurs with nasal augmentation,followed by glabellar wrinkle treatment.While injected autologous fat predominantly occludes the proximal portion of the ophthalmic artery,hyaluronic acid fillers obstruct the ophthalmic artery comparatively distally.Treatment interventions include thrombolysis,hyperbaric oxygen therapy,oral aspirin,cobamamide and acetazolamide and administration of corticosteroids.However,most studies show a poor prognosis in the form of partial or no recovery of vision.Hence,prevention is of paramount importance.A high index of suspicion is also warranted on the part of both those administering as well as receiving injections of facial fillers to prevent potentially vision-threatening complications of this seemingly innocuous procedure.

Applications of artificial intelligence in geothermal resource exploration: A review

Artificial intelligence (AI) has become increasingly important in geothermal exploration,significantly improving the efficiency of resource identification.This review examines current AI applications,focusing on the algorithms used,the challenges addressed,and the opportunities created.In addition,the review highlights the growth of machine learning applications in geothermal exploration over the past decade,demonstrating how AI has improved the analysis of subsurface data to identify potential resources.AI techniques such as neural networks,support vector machines,and decision trees are used to estimate subsurface temperatures,predict rock and fluid properties,and identify optimal drilling locations.In particular,neural networks are the most widely used technique,further contributing to improved exploration efficiency.However,the widespread adoption of AI in geothermal exploration is hindered by challenges,such as data accessibility,data quality,and the need for tailored data science training for industry professionals.Furthermore,the review emphasizes the importance of data engineering methodologies,data scaling,and standardization to enable the development of accurate and generalizable AI models for geothermal exploration.It is concluded that the integration of AI into geothermal exploration holds great promise for accelerating the development of geothermal energy resources.By effectively addressing key challenges and leveraging AI technologies,the geothermal industry can unlock cost‐effective and sustainable power generation opportunities.

Robust blind image watermarking based on interest points

Digital watermarking technology plays an essential role in the work of anti-counterfeiting and traceability.However,image watermarking algorithms are weak against hybrid attacks,especially geometric attacks,such as cropping attacks,rotation attacks,etc.We propose a robust blind image watermarking algorithm that combines stable interest points and deep learning networks to improve the robustness of the watermarking algorithm further.First,to extract more sparse and stable interest points,we use the Superpoint algorithm for generation and design two steps to perform the screening procedure.We first keep the points with the highest possibility in a given region to ensure the sparsity of the points and then filter the robust interest points by hybrid attacks to ensure high stability.The message is embedded in sub-blocks centered on stable interest points using a deep learning-based framework.Different kinds of attacks and simulated noise are added to the adversarial training to guarantee the robustness of embedded blocks.We use the ConvNext network for watermark extraction and determine the division threshold based on the decoded values of the unembedded sub-blocks.Through extensive experimental results,we demonstrate that our proposed algorithm can improve the accuracy of the network in extracting information while ensuring high invisibility between the embedded image and the original cover image.Comparison with previous SOTA work reveals that our algorithm can achieve better visual and numerical results on hybrid and geometric attacks.

Research on blind source separation of operation sounds of metro power transformer through an Adaptive Threshold REPET algorithm

Purpose–The safe operation of the metro power transformer directly relates to the safety and efficiency of the entire metro system.Through voiceprint technology,the sounds emitted by the transformer can be monitored in real-time,thereby achieving real-time monitoring of the transformer’s operational status.However,the environment surrounding power transformers is filled with various interfering sounds that intertwine with both the normal operational voiceprints and faulty voiceprints of the transformer,severely impacting the accuracy and reliability of voiceprint identification.Therefore,effective preprocessing steps are required to identify and separate the sound signals of transformer operation,which is a prerequisite for subsequent analysis.Design/methodology/approach–This paper proposes an Adaptive Threshold Repeating Pattern Extraction Technique(REPET)algorithm to separate and denoise the transformer operation sound signals.By analyzing the Short-Time Fourier Transform(STFT)amplitude spectrum,the algorithm identifies and utilizes the repeating periodic structures within the signal to automatically adjust the threshold,effectively distinguishing and extracting stable background signals from transient foreground events.The REPET algorithm first calculates the autocorrelation matrix of the signal to determine the repeating period,then constructs a repeating segment model.Through comparison with the amplitude spectrum of the original signal,repeating patterns are extracted and a soft time-frequency mask is generated.Findings–After adaptive thresholding processing,the target signal is separated.Experiments conducted on mixed sounds to separate background sounds from foreground sounds using this algorithm and comparing the results with those obtained using the FastICA algorithm demonstrate that the Adaptive Threshold REPET method achieves good separation effects.Originality/value–A REPET method with adaptive threshold is proposed,which adopts the dynamic threshold adjustment mechanism,adaptively calculates the threshold for blind source separation and improves the adaptability and robustness of the algorithm to the statistical characteristics of the signal.It also lays the foundation for transformer fault detection based on acoustic fingerprinting.

Prevalence and Factors Associated with Refractive Errors among University Students at Mbarara University of Science and Technology, Uganda

Introduction: WHO estimated that uncorrected refractive errors are the leading cause of visual impairment and second leading cause of blindness globally. University students are prone to developing refractive errors due to their curriculum that requires a lot of near work affecting their performance and quality of life unknowingly. Genetic and environmental factors are thought to play a role in the development of refractive errors. This study addresses the paucity of knowledge about refractive errors among university students in East Africa, providing a foundation for further research. Objectives: To determine the prevalence and factors associated with refractive errors among students in the Faculty of Medicine at Mbarara University of Science and Technology. Methodology: This was a cross-sectional descriptive and analytical study in which 368 undergraduate students selected using random sampling were assessed for refractive errors from March 2021-July 2021. Eligible participants were recruited and their VA assessment done after answering a questionnaire. Students whose VA improved on pin hole had subjective retinoscopy and results were compiled and imported to STATA 14 for analysis. Results: The prevalence of refractive errors was 26.36% with (95% CI) among university students especially myopia. Myopia is most predominant at 60%, followed by 37% Astigmatism and hyperopia of 3% among medical students. Astigmatism consisted of largely myopic astigmatism 72% (26) and 28% (10) compound/mixed astigmatism only. Student positive family history of refractive error was found to have a statistically significant relationship with refractive errors with AOR 1.68 (1.04 - 2.72) (95% CI) and P (0.032). Conclusion: The prevalence of refractive errors among university students, especially myopia, was found to be high and family history was associated with students having refractive errors.

Cost of Medical Treatment for Primary Open-Angle Glaucoma in Relation to Patients’ Income and Its Impact on the Prognosis of the Disease, in Bouaké University Hospital

Introduction: Medical treatment for POAG is continuous and lifelong treatment. The aim of this study was to evaluate the relationship between the cost of this treatment and patients’ income and the impact of this relationship on treatment compliance. Materials and Methods: Prospective cross-sectional study with a descriptive aim covering sociodemographic data, average incomes, and direct and indirect costs of treatment of 57 patients followed for POAG during the period from January 1, 2012, to December 31, 2016 (5 years). Results: The patients were aged 25 to 77 years (mean = 54.4 years) with a male predominance (sex ratio = 1.5). Retirees were the most represented (26.32%), followed by workers in the informal sector (14.04%) and housewives (12.28%). Patients who had an annual income less than or equal to 900,000 CFA francs (€1370.83) per year represented 56.14% and those who did not have health coverage represented 57.89%. The treatment was monotherapy (64.91%), dual therapy (31.58%) or triple therapy (3.05%) and the average ratio of “annual cost of treatment to annual income” was 0.56 with for maximum 2.23 and 0.02 as minimum. Patients who considered the cost of treatment unbearable for their income represented 78.95%. Conclusion: Prevention of blindness due to glaucoma requires early detection but also the establishment of health coverage mechanisms to improve compliance with medical treatment. In addition, consideration should be given to the development of glaucoma surgery in our country, the indication of which could be the first intention in certain patients, considering for those patients, the geographical and financial accessibility of medical treatment. .

Discussion on the application prospect of the transient electromagnetic method based on the dual launcher and mine advanced detection

The dual transmitter implements the equivalent anti-magnetic flux transient electromagnetic method, which can effectively reduce the scope of the transient electromagnetic detection blind area. However, this method is rarely reported in the detection of pipelines in urban geophysical exploration and the application of coal mines. Based on this, this paper realizes the equivalent anti-magnetic flux transient electromagnetic method based on the dual launcher. The suppression effect of this method on the blind area is analyzed by physical simulation. And the detection experiment of underground pipelines is carried out outdoors. The results show that the dual launcher can significantly reduce the turn-off time, thereby effectively reducing the impact of the blind area on the detection results, and the pipeline detection results verify the device’s effectiveness. Finally, based on the ground experimental results, the application prospect of mine advanced detection is discussed. Compared with other detection fields, the formation of blind areas is mainly caused by the equipment. If the dual launcher can be used to reduce the blind area, the accuracy of advanced detection can be improved more effectively. The above research results are of great significance for improving the detection accuracy of the underground transient electromagnetic method.

Image Processing for Denoising Using Composite Adaptive Filtering Methods Based on RMSE

As one of the carriers for human communication and interaction, images are prone to contamination by noise during transmission and reception, which is often uncontrollable and unknown. Therefore, how to denoise images contaminated by unknown noise has gradually become one of the research focuses. In order to achieve blind denoising and separation to restore images, this paper proposes a method for image processing based on Root Mean Square Error (RMSE) by integrating multiple filtering methods for denoising. This method includes Wavelet Filtering, Gaussian Filtering, Median Filtering, Mean Filtering, Bilateral Filtering, Adaptive Bandpass Filtering, Non-local Means Filtering and Regularization Denoising suitable for different types of noise. We can apply this method to denoise images contaminated by blind noise sources and evaluate the denoising effects using RMSE. The smaller the RMSE, the better the denoising effect. The optimal denoising result is selected through comprehensively comparing the RMSE values of all methods. Experimental results demonstrate that the proposed method effectively denoises and restores images contaminated by blind noise sources.

Exploring the meaning of care among lived experiences of patients with blindness:an interpretive phenomenological study

Objective:To explore the meaning of care experienced by people with blindness in hospitals.Methods:Interpretive phenomenology along with the 6-step method of van Manen was used to conduct the study.Using purposeful sampling,15 people with legal blindness were interviewed.Thematic analysis was used to isolate the meaning of care.Results:Five themes emerged:(a)nurses in the eyes of patients with blindness;(b)negligence in the caring moments;(c)being cared for in ambiguity;(d)Uncoordinated care;and(e)Psychological discomfor t.These sub-themes were condensed into an overarching theme titled as“marginalized patients inside the stereotypical healthcare system.”Conclusions:Lived experiences of patients with blindness revealed that hospitals provide stereotypic or inappropriate care for this minority group in society.Health professionals par ticularly nurses should be skilled to provide person-centered and coordinated care for patients with blindness.

基于拟态防御的VPN流量劫持防御技术

VPN技术能够有效保障通信流量的保密性和完整性,但是近年来出现的名为blind in/on-path的流量劫持攻击利用VPN协议规则,通过将伪造报文注入加密隧道的方式来实施攻击,严重威胁了VPN技术的安全性。针对此类威胁,提出了基于拟态防御的VPN流量劫持防御技术,并设计了拟态VPN架构(Mimic VPN,M-VPN)。该架构由选调器和包含多个异构的VPN加解密节点的节点池组成。首先选调器根据节点的可信度动态地选取若干加解密节点,来并行处理加密流量;然后对各加解密节点的处理结果进行综合裁决;最后将裁决结果作为响应报文以及更新可信度的依据。通过对来自不同节点的同一响应进行裁决,有效阻止了攻击者注入伪造报文。实验仿真结果表明,相比传统的VPN架构,M-VPN可以降低blind in/on-path攻击成功率约12个数量级。

A robust deformed convolutional neural network(CNN)for image denoising

Due to strong learning ability,convolutional neural networks(CNNs)have been developed in image denoising.However,convolutional operations may change original distributions of noise in corrupted images,which may increase training difficulty in image denoising.Using relations of surrounding pixels can effectively resolve this problem.Inspired by that,we propose a robust deformed denoising CNN(RDDCNN)in this paper.The proposed RDDCNN contains three blocks:a deformable block(DB),an enhanced block(EB)and a residual block(RB).The DB can extract more representative noise features via a deformable learnable kernel and stacked convolutional architecture,according to relations of surrounding pixels.The EB can facilitate contextual interaction through a dilated convolution and a novel combination of convolutional layers,batch normalisation(BN)and ReLU,which can enhance the learning ability of the proposed RDDCNN.To address long-term dependency problem,the RB is used to enhance the memory ability of shallow layer on deep layers and construct a clean image.Besides,we implement a blind denoising model.Experimental results demonstrate that our denoising model outperforms popular denoising methods in terms of qualitative and quantitative analysis.Codes can be obtained at https://github.com/hellloxiaotian/RDDCNN.