Deciphering the Hidden Secrets between the Early Skin Wrinkling & the Metabolic (X) Syndrome with the Possible Reversal of This Process at the Molecular Level

The aging process is a group of degenerative changes that physiologically occur in most of the people in the elderly. This affects one or more of the human body systems. The treatment of diseases related to the aging process has a huge impact on the economy of all nations. Aging of the skin comes on the top and despite that, the results of the already present lines of treatment are not always satisfactory. This acts as a stimulus for us to dig deeper to discover the root causes of the premature aging of the skin. This was simply caused by the accumulation of repeated minute damage to the internal structure skin. In other words, if the degree of minute damage is more than the capacity of the skin to repair, the repeated micro-damage is presented in the long run as a skin wrinkling. Moreover, the skin acts as a mirror that reflects the internal structures of the human body. Thus, the more degenerative changes in the human body systems, the more the skin could become wrinkled. Our strategy to prevent or at least slow down the aging process of the skin depends on 2 main steps;the 1st is to reduce the micro-damage as can as possible, and the 2nd is to enhance the capacity of tissue regeneration to be able to reverse the already present damaged skin. As the 2 processes are synchronized with each other, this strategy would be considered the ideal for prevention of skin wrinkling especially premature ones. This not only reverses premature skin wrinkling but also protects it from future wrinklings. This review sharply pointed out the role of the functional collagen of the dermal layer of the skin in the prevention of skin wrinklings. Therefore, it would be the target to study how collagen works in the complex machinery of the dermal layer of the skin. This concept deeply believes that the recovery of dermal collagen has a much better effect than simply ingesting collagen or receiving a topical collagen booster. .

Emoti-Shing: Detecting Vishing Attacks by Learning Emotion Dynamics through Hidden Markov Models

This study examines vishing, a form of social engineering scam using voice communication to deceive individuals into revealing sensitive information or losing money. With the rise of smartphone usage, people are more susceptible to vishing attacks. The proposed Emoti-Shing model analyzes potential victims’ emotions using Hidden Markov Models to track vishing scams by examining the emotional content of phone call audio conversations. This approach aims to detect vishing scams using biological features of humans, specifically emotions, which cannot be easily masked or spoofed. Experimental results on 30 generated emotions indicate the potential for increased vishing scam detection through this approach.

Switchable hidden spin polarization and negative Poisson's ratio in two-dimensional antiferroelectric wurtzite crystals

Two-dimensional(2D)antiferroelectric materials have raised great research interest over the last decade.Here,we reveal a type of 2D antiferroelectric(AFE)crystal where the AFE polarization direction can be switched by a certain degree in the 2D plane.Such 2D functional materials are realized by stacking the exfoliated wurtzite(wz)monolayers with“self-healable”nature,which host strongly coupled ferroelasticity/antiferroelectricity and benign stability.The AFE candidates,i.e.,Zn X and Cd X(X=S,Se,Te),are all semiconductors with direct bandgap atΓpoint,which harbors switchable antiferroelectricity and ferroelasticity with low transition barriers,hidden spin polarization,as well as giant in-plane negative Poisson's ratio(NPR),enabling the co-tunability of hidden spin characteristics and auxetic magnitudes via AFE switching.The 2D AFE wz crystals provide a platform to probe the interplay of 2D antiferroelectricity,ferroelasticity,NPR,and spin effects,shedding new light on the rich physics and device design in wz semiconductors.

Existence of hidden attractors in nonlinear hydro-turbine governing systems and its stability analysis

This work studies the stability and hidden dynamics of the nonlinear hydro-turbine governing system with an output limiting link,and propose a new six-dimensional system,which exhibits some hidden attractors.The parameter switching algorithm is used to numerically study the dynamic behaviors of the system.Moreover,it is investigated that for some parameters the system with a stable equilibrium point can generate strange hidden attractors.A self-excited attractor with the change of its parameters is also recognized.In addition,numerical simulations are carried out to analyze the dynamic behaviors of the proposed system by using the Lyapunov exponent spectra,Lyapunov dimensions,bifurcation diagrams,phase space orbits,and basins of attraction.Consequently,the findings in this work show that the basins of hidden attractors are tiny for which the standard computational procedure for localization is unavailable.These simulation results are conducive to better understanding of hidden chaotic attractors in higher-dimensional dynamical systems,and are also of great significance in revealing chaotic oscillations such as uncontrolled speed adjustment in the operation of hydropower station due to small changes of initial values.

Reliability and validity of the hidden hunger assessment scale in China-revised for high school students

Objective:Hidden hunger remains a severe public health problem that affects millions of people worldwide.In China,challenges related to dietary imbalance and hidden hunger persist.Micronutrient inadequacy deserves more attention among adolescents,given its vital role in their growth and development;however,this problem appears to have been largely ignored.High school students,in particular,are often at a high risk of hidden hunger but have limited assessment tools available.Therefore,this study aims to revise the hidden hunger assessment scale for high school students(HHAS-HSS)in China and assess its reliability and validity.Methods:Based on a literature review,expert consultation,pre-experiment,and formal survey,a hidden hunger assessment scale was revised for high school students.The formal survey involved 9336 high school students in 11 of the 16 cities in Anhui Province,China,and 9038 valid questionnaires were collected and included in the analysis.The item analysis,internal consistency reliability,test-retest reliability,content validity,exploratory factor analysis,and confirmatory factor analysis of the HHAS-HSS were examined.Results:The HHAS-HSS included a total of 4 dimensions and 12 items:"vegetables and food diversity"(three items),"fruits and dairy products"(three items),"micronutrient-dense foods"(four items),and"health condition and eating habits"(two items).The results showed a Cronbach's alpha of 0.758,a split-half reliability of 0.829,and a test-retest reliability of o.793,indicating good internal consistency.Using the Bartlett's test and Kaiser-Meyer-Olkin test(KMO)to test the exploratory factor analysis presented a four-factor model of the HHAS-HSS,the KMO0 value was 0.820(P<0.001),which indicated the possibility for factor confirmatory factor analysis.Using the maximum variance rotation method,four factors were obtained,and the cumulative variance explained rate was 57.974%.Confirmatory factor analysis also supported the division of the scale into four dimensions,and the fitting indices were x^(2)=1417.656,x^(2)/df=29.534,goodness-of-fit index=0.974,adjusted goodnessof-fit index=0.958,parsimonious goodness-of-fit index=0.600,normed fit index=0.938,incremental fit index=0.940,Tucker-Lewis index=0.917,comparative fit index=0.939,and root mean square error of approximation=0.056.Except for x^(2)/df,all the indices reached the fitting standard,and the above results showed that the construct validity of the scale reached an acceptable level.Conclusions:The HHAS-HSS has good validity and reliability for Chinese high school students.It is a convenient self-report measure of hidden hunger risk.

Hidden Hierarchy Based on Cipher-Text Attribute Encryption for IoT Data Privacy in Cloud

Most research works nowadays deal with real-time Internetof Things (IoT) data. However, with exponential data volume increases,organizations need help storing such humongous amounts of IoT data incloud storage systems. Moreover, such systems create security issues whileefficiently using IoT and Cloud Computing technologies. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has the potential to make IoT datamore secure and reliable in various cloud storage services. Cloud-assisted IoTssuffer from two privacy issues: access policies (public) and super polynomialdecryption times (attributed mainly to complex access structures). We havedeveloped a CP-ABE scheme in alignment with a Hidden HierarchyCiphertext-Policy Attribute-Based Encryption (HH-CP-ABE) access structure embedded within two policies, i.e., public policy and sensitive policy.In this proposed scheme, information is only revealed when the user’sinformation is satisfactory to the public policy. Furthermore, the proposedscheme applies to resource-constrained devices already contracted tasks totrusted servers (especially encryption/decryption/searching). Implementingthe method and keywords search resulted in higher access policy privacy andincreased security. The new scheme introduces superior storage in comparisonto existing systems (CP-ABE, H-CP-ABE), while also decreasing storage costsin HH-CP-ABE. Furthermore, a reduction in time for key generation canalso be noted.Moreover, the scheme proved secure, even in handling IoT datathreats in the Decisional Bilinear Diffie-Hellman (DBDH) case.

Application of"Six Thinking Hats"in the Investigation and Improvement of Hidden Dangers in Food Safety

With the development of economy,people's living standards are constantly improving,and the requirements for food safety are getting higher and higher.The Food Safety Law stipulates that enterprises should implement the main responsibility of food safety,and the investigation and improvement of food safety hazards plays an important role in improving the food safety management level of enterprises and reducing food safety risks.This paper combines the innovative thinking mode of six thinking hats with food safety,discusses the application mode of six thinking hats in food safety investigation and improvement,and hopes to improve food safety level through this way.

Hidden Hearing Loss: Causes, Current Knowledge, and Future Directions

Introduction: Hidden hearing loss (HHL) is a type of auditory disorder that affects the auditory neural processing and hearing sensitivity in subjects with normal hearing thresholds. Unlike central auditory processing disorders, HHL happens when the cochlea (the peripheral auditory organ) is affected. There are several known risk factors to HHL which includes noise exposure, ototoxic drugs, and peripheral neuropathies, and age. Recent studies have shed light on this type of hearing loss, its etiology, prevalence, and how it can affect the auditory acuity in humans. Methods: This paper covers the current research regarding HHL, its causes, the different mechanisms involved in this disorder, and the diagnosis and potential treatments related to it. We will delve deeply into different researches concerning HHL. 4 articles from 285 were selected focusing on normal hearing individuals with bad speech intelligibility were discussed in this paper. In addition, articles discussing the effects of noise exposure on hearing impaired individuals were not considered as this study solely aims to focus on normal hearing sensitivity individuals with HHL, resulting in 4 articles from 285. Results: Numerous literatures over the decades have suggested that HHL is due to the degeneration of cochlear ribbon synapses, or hair cells synapses without hair cell damage. Their association with HHL was noted several times through this study, whether we were studying the effect of noise exposure, of age, or of ototoxicity. In all cases, no significant hair cell damage was observed, and normal thresholds were recovered. However, a decline in the amplitude of Auditory Brainstem Response (ABR) peak I from auditory nerve (AN) responses in noise exposed subjects and a decline in compound action potential (CAP) was measured when certain drugs were applied to the round window of Guinea pigs. Conclusion: Most studies, have proven that cochlear synaptophysin is the major contributor to noise induced, age, and ototoxic related HHL. There are several audiometric tests that were used to help identify HHL including Puretone audiometry in background noise, ABR, CAP, Distortion Product Otoacoustic Emission (DPOAE).

Prediction of Hidden Blood Loss During Posterior Spinal Surgery

Objective Identification of the risk factors for extraordinary hidden blood loss(HBL) could clarify the underlying causes and provide more appropriate management. This study aims to identify the predictors of HBL in spinal surgery.Methods Medical records were retrospectively retrieved to collect the data of patients who undergoing posterior thoracic and lumbar fusion surgery or scoliosis surgery. Demographic information, perioperative visible blood loss volume, as well as laboratory results were recorded. The patients receiving fusion surgery or scoliosis surgery were further divided into the HBL positive subgroup and the HBL negative subgroup. Differences in the variables between the groups were then analyzed. Binary logistic regression analysis was performed to determine independent risk factors associated with HBL.Results For patients undergoing posterior spinal surgery, the independent risk factors associated with HBL were autologous transfusion(for fusion surgery P = 0.011, OR: 2.627, 95%CI: 1.574-2.782; for scoliosis surgery P < 0.001, OR: 2.268, 95%CI: 2.143-2.504) and allogeneic transfusion(for fusion surgery P < 0.001, OR: 6.487, 95%CI: 2.349-17.915; for scoliosis surgery P < 0.001, OR: 3.636, 95%CI: 2.389-5.231).Conclusion Intraoperative blood transfusion might be an early-warning indicator for perioperative HBL.

基于启发式查询词选择算法的Hidden Web获取研究

Hidden Web因为其隐蔽性而难以直接抓取,因此成为信息检索研究的一个新领域。提出了一种获取Hidden Web信息的方法,讨论了实现的关键技术。通过设计提出的启发式查询词选择算法,提高了抓取的效率。实验证明了该模型和算法的有效性。

Ontology mapping based on hidden Markov model

The existing ontology mapping methods mainly consider the structure of the ontology and the mapping precision is lower to some extent. According to statistical theory, a method which is based on the hidden Markov model is presented to establish ontology mapping. This method considers concepts as models, and attributes, relations, hierarchies, siblings and rules of the concepts as the states of the HMM, respectively. The models corresponding to the concepts are built by virtue of learning many training instances. On the basis of the best state sequence that is decided by the Viterbi algorithm and corresponding to the instance, mapping between the concepts can be established by maximum likelihood estimation. Experimental results show that this method can improve the precision of heterogeneous ontology mapping effectively.

TONE MODELING BASED ON HIDDEN CONDITIONAL RANDOM FIELDS AND DISCRIMINATIVE MODEL WEIGHT TRAINING

The use of hidden conditional random fields （HCRFs） for tone modeling is explored. The tone recognition performance is improved using HCRFs by taking advantage of intra-syllable dynamic, inter-syllable dynamic and duration features. When the tone model is integrated into continuous speech recognition, the discriminative model weight training （DMWT） is proposed. Acoustic and tone scores are scaled by model weights discriminatively trained by the minimum phone error （MPE） criterion. Two schemes of weight training are evaluated and a smoothing technique is used to make training robust to overtraining problem. Experiments show that the accuracies of tone recognition and large vocabulary continuous speech recognition （LVCSR） can be improved by the HCRFs based tone model. Compared with the global weight scheme, continuous speech recognition can be improved by the discriminative trained weight combinations.

Hidden Web信息获取

如今Web上越来越多的信息可以通过查询接口获得,但为了获取某Hidden Web站点的页面,用户不得不键入一系列的关键词。由于没有直接指向Hidden Web页面的静态链接,当前大多搜索引擎不能发现和索引这些页面。然而,研究表明,由Hidden Web站点提供的高质量的信息对许多用户来说非常有价值。文章通过研究针对特定类型的表单,建立一个有效的Hidden Web爬虫,以便获取Hidden Web后台数据库信息。

Differential colour-ring loss among Dalmatian Pelican(Pelecanus crispus) colonies and its consequence on survival estimates

The analysis of bird ringing data often comes with some potential sources of error and bias,as ring wear and/or loss could affect mark-recapture analyses and produce erroneous estimates of survival.Furthermore,ring wear and loss rates may differ between and within species based on the habitat they use or the species’ life-history traits and behaviour as well as the type of the ring.In this study we use resighting data from a long-term double marking experiment to directly estimate the rate of colour-ring loss among different Dalmatian Pelican colonies over time,evaluate any possible factors that could contribute to differential ring loss and assess how it may bias the results of mark-resighting analyses.Based on 14,849 resightings from 1275 individuals and using multi-state continuous-time hidden Markov models(HMMs) we showed that probability of ring loss was markedly different among colonies,ranging from 0.10 to 0.42 within the first year of marking,whereas the cumulative probability of losing a ring after ten years ranged 0.64 to 0.99.These rates are among the highest estimated when compared to previous studies in waterbirds.Our approach assessing the intra-specific variance in ring loss provided several factors potentially involved,such as the use of glue and the fledgling age accuracy and we could further hypothesise the effect of environmental factors.Finally,our results showed that ring loss can be a significant challenge for the assessment of the species’ population dynamics using mark-recapture methods as survival was consistently underestimated when not accounting for ring loss and varied significantly among different colonies.

Optimal state and branch sequence based parameter estimation of continuous hidden Markov model

A parameter estimation algorithm of the continuous hidden Markov model isintroduced and the rigorous proof of its convergence is also included. The algorithm uses theViterbi algorithm instead of K-means clustering used in the segmental K-means algorithm to determineoptimal state and branch sequences. Based on the optimal sequence, parameters are estimated withmaximum-likelihood as objective functions. Comparisons with the traditional Baum-Welch and segmentalK-means algorithms on various aspects, such as optimal objectives and fundamentals, are made. Allthree algorithms are applied to face recognition. Results indicate that the proposed algorithm canreduce training time with comparable recognition rate and it is least sensitive to the training set.So its average performance exceeds the other two.

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.

IMPROVEMENTS IN HIDDEN LINE REMOVAL ALGORITHM FOR BI-PARAMETRIC SURFACES

A hidden line removal algorithm for bi parametric surfaces is presented and illustrated by some experimental results. The enclosure test is done using area coordinates. A technique of moving box of encirclement is presented. It is found that the algorithm is of general purpose, requires minimal computer storage, has high accuracy and simplicity, and is very easy to be implemented on a computer.

Malus’ Law Derived from Deterministic Particle Behavior

A polarized beam of energy is usually interpreted as a set of particles, all having the same polarization state. Difference in behavior between the one and the other particle is then explained by a number of counter-intuitive quantum mechanical concepts like probability distribution, superposition, entanglement and quantized spin. Alternatively, I propose that a polarized beam is composed of a set of particles with a cosine distribution of polarization angles within a polarization area. I show that Malus’ law for the intensity of a beam of polarized light can be derived in a straightforward manner from this distribution. I then show that none of the above-mentioned counter-intuitive concepts are necessary to explain particle behavior and that the ontology of particles, passing through a polarizer, can be easily and intuitively understood. I conclude by formulating some questions for follow-up research.

Study on Problems and Countermeasures of English Hidden Curriculum Construction in Higher Vocational Colleges in the Era of “Internet Plus”

As the extension and supplement of explicit curriculum,the English hidden curriculum in higher vocational colleges plays animportant role in cultivating students' behaviors,stimulate their interest and arouse their enthusiasm,initiative and creativity in learningEnglish.This paper analyzes the problems of English hidden curriculum construction in higher vocational colleges under the back-ground o"fInternet plus",and puts forward some corresponding countermeasures to bring the role of college English hidden curriculuminto full play.

A Study on the Impact of Voice-to-Text Technology on Academic Achievement of the Hearing-Impaired

Hearing loss is a significant barrier to academic achievement,with hearing-impaired(HI)individuals often facing challenges in speech recognition,language development,and social interactions.Lip-reading,a crucial skill for HI individuals,is essential for effective communication and learning.However,the COVID-19 pandemic has exacerbated the challenges faced by HI individuals,with the face masks hindering lip-reading.This literature review explores the relationship between hearing loss and academic achievement,highlighting the importance of lip-reading and the potential of artificial intelligence(AI)techniques in mitigating these challenges.The introduction of Voice-to-Text(VtT)technology,which provides real-time text captions,can significantly improve speech recognition and academic performance for HI students.AI models,such as Hidden Markov models and Transformer models,can enhance the accuracy and robustness of VtT technology in diverse educational settings.Furthermore,VtT technology can facilitate better teacher-student interactions,provide transcripts of lectures and classroom discussions,and bridge the gap in standardized testing performance between HI and hearing students.While challenges and limitations exist,the successful implementation of VtT technology can promote inclusive education and enhance academic achievement.Future research directions include popularizing VtT technology,addressing technological barriers,and customizing VtT systems to cater to individual needs.