Achieving Enhanced Dielectric and Energy Storage Performance in Poly(vinyl chloride-glycidyl methacrylate) through Tuning Interchain Interactions.

Glassy polymer dielectrics exhibit significant advantages in energy storage density and discharge efficiency; however, their potential application in thin-film capacitors is limited by the complexity of the production process, rising costs, and processing challenges arising from the brittleness of the material. In this study, a small amount of the polar monomer glycidyl methacrylate (GMA) was copolymerized with vinyl chloride (VC) using a highly integrated and precisely controlled process. This effectively facilitated the bulk synthesis of P(VC-GMA) copolymers, aimed at enhancing the dielectric properties and energy storage capabilities of the copolymer. Moreover, the incorporation of GMA into PVC induces significant alterations in the structural sequence of the copolymer, resulting in an enhancement of interchain interactions that ultimately contribute to an increase in the modulus and improved breakdown strength. With a GMA content of 2.4 mol %, P(VC-GMA) exhibits a significant enhancement in discharge energy density, surpassing that of a pure PVC copolymer, while maintaining high discharge efficiency and stability. The finding of this study paves the way for future advancements in high-energy-storage polymer dielectrics, thereby expanding the scope of advanced dielectric materials.

Utilizing Machine Learning Techniques to Predict the Efficacy of Aerobic Exercise Intervention on Young Hypertensive Patients Based on Cardiopulmonary Exercise Testing.

Recently, the incidence of hypertension has significantly increased among young adults. While aerobic exercise intervention (AEI) has long been recognized as an effective treatment, individual differences in response to AEI can seriously influence clinicians' decisions. In particular, only a few studies have been conducted to predict the efficacy of AEI on lowering blood pressure (BP) in young hypertensive patients. As such, this paper aims to explore the implications of various cardiopulmonary metabolic indicators in the field by mining patients' cardiopulmonary exercise testing (CPET) data before making treatment plans. CPET data are collected "breath by breath" by using an oxygenation analyzer attached to a mask and then divided into four phases: resting, warm-up, exercise, and recovery. To mitigate the effects of redundant information and noise in the CPET data, a sparse representation classifier based on analytic dictionary learning was designed to accurately predict the individual responsiveness to AEI. Importantly, the experimental results showed that the model presented herein performed better than the baseline method based on BP change and traditional machine learning models. Furthermore, the data from the exercise phase were found to produce the best predictions compared with the data from other phases. This study paves the way towards the customization of personalized aerobic exercise programs for young hypertensive patients.

Influence of dipole and intermolecular interaction on the tuning dielectric and energy storage properties of polystyrene-based polymers.

A dielectric polymer with high energy density is in high demand in modern electric and electronic systems. The current polymer dielectrics are facing the tradeoff between high energy density and low energy loss. Although many efforts have been devoted to solving the problem by modifying biaxially oriented polypropylene (BOPP), poly(vinylidene fluoride) (PVDF) and glassy polymers, limited success has been achieved. In the present work, we disperse the high polar nitrile units in a low polar polystyrene (PSt) matrix to avoid the strong coupling force among the adjacent polar groups and reduce the relaxation-induced high dielectric loss. In addition, the possible charge transportation offered by phenyl groups could be blocked by the enlarged bandgap. Notably, the induced polarization is established between the nitrile and phenyl groups, which may lead to the copolymer chain being more densely packed. As a result, excellent energy storage performances, including the high energy density and low loss, are achieved in the resultant poly(styrene-co-acrylonitrile) (AS). For instance, AS-4 exhibits a Ue of 11.4 J cm-3 and η of 91% at ambient temperature and 550 MV m-1. Manipulating the dipole polarization in the low polar glassy polymer matrix is verified to be a facile strategy for the design of a high-energy storage dielectric polymer.

Additive effects of simulated microgravity and ionizing radiation in cell death, induction of ROS and expression of RAC2 in human bronchial epithelial cells.

Radiation and microgravity are undoubtedly two major factors in space environment that pose a health threat to astronauts. However, the mechanistic study of their interactive biological effects is lacking. In this study, human lung bronchial epithelial Beas-2B cells were used to study the regulation of radiobiological effects by simulated microgravity (using a three-dimensional clinostat). It was found that simulated microgravity together with radiation induced drop of survival fraction, proliferation inhibition, apoptosis, and DNA double-strand break formation of Beas-2B cells additively. They also additively induced Ras-related C3 botulinum toxin substrate 2 (RAC2) upregulation, leading to increased NADPH oxidase activity and increased intracellular reactive oxygen species (ROS) yield. The findings indicated that simulated microgravity and ionizing radiation presented an additive effect on cell death of human bronchial epithelial cells, which was mediated by RAC2 to some extent. The study provides a new perspective for the better understanding of the compound biological effects of the space environmental factors.

A partial encryption algorithm for medical images based on quick response code and reversible data hiding technology.

BACKGROUND: Medical image data, like most patient information, have a strong requirement for privacy and confidentiality. This makes transmitting medical image data, within an open network, problematic, due to the aforementioned issues, along with the dangers of data/information leakage. Possible solutions in the past have included the utilization of information-hiding and image-encryption technologies; however, these methods can cause difficulties when attempting to recover the original images. METHODS: In this work, we developed an algorithm for protecting medical image key regions. Coefficient of variation is first employed to identify key regions, a.k.a. image lesion areas; then additional areas are processed as blocks and texture complexity is analyzed. Next, our novel reversible data-hiding algorithm embeds lesion area contents into a high-texture area, after which an Arnold transformation is utilized to protect the original lesion information. After this, we use image basic information ciphertext and decryption parameters to generate a quick response (QR) code used in place of original key regions. RESULTS: The approach presented here allows for the storage (and sending) of medical image data within open network environments, while ensuring only authorized personnel are able to recover sensitive patient information (both image and meta-data) without information loss. DISCUSSION: Peak signal to noise ratio and the Structural Similarity Index measures show that the algorithm presented in this work can encrypt and restore original images without information loss. Moreover, by adjusting the threshold and the Mean Squared Error, we can control the overall quality of the image: the higher the threshold, the better the quality and vice versa. This allows the encryptor to control the amount of degradation as, at appropriate amounts, degradation aids in the protection of the image. CONCLUSIONS: As shown in the experimental results, the proposed method allows for (a) the safe transmission and storage of medical image data, (b) the full recovery (no information loss) of sensitive regions within the medical image following encryption, and (c) meta-data about the patient and image to be stored within and recovered from the public image.

Development of a support vector machine learning and smart phone Internet of Things-based architecture for real-time sleep apnea diagnosis.

BACKGROUND: The breathing disorder obstructive sleep apnea syndrome (OSAS) only occurs while asleep. While polysomnography (PSG) represents the premiere standard for diagnosing OSAS, it is quite costly, complicated to use, and carries a significant delay between testing and diagnosis. METHODS: This work describes a novel architecture and algorithm designed to efficiently diagnose OSAS via the use of smart phones. In our algorithm, features are extracted from the data, specifically blood oxygen saturation as represented by SpO2. These features are used by a support vector machine (SVM) based strategy to create a classification model. The resultant SVM classification model can then be employed to diagnose OSAS. To allow remote diagnosis, we have combined a simple monitoring system with our algorithm. The system allows physiological data to be obtained from a smart phone, the data to be uploaded to the cloud for processing, and finally population of a diagnostic report sent back to the smart phone in real-time. RESULTS: Our initial evaluation of this algorithm utilizing actual patient data finds its sensitivity, accuracy, and specificity to be 87.6%, 90.2%, and 94.1%, respectively. DISCUSSION: Our architecture can monitor human physiological readings in real time and give early warning of abnormal physiological parameters. Moreover, after our evaluation, we find 5G technology offers higher bandwidth with lower delays ensuring more effective monitoring. In addition, we evaluate our algorithm utilizing real-world data; the proposed approach has high accuracy, sensitivity, and specific, demonstrating that our approach is very promising. CONCLUSIONS: Experimental results on the apnea data in University College Dublin (UCD) Database have proven the efficiency and effectiveness of our methodology. This work is a pilot project and still under development. There is no clinical validation and no support. In addition, the Internet of Things (IoT) architecture enables real-time monitoring of human physiological parameters, combined with diagnostic algorithms to provide early warning of abnormal data.

Grafting PMMA onto P(VDF-TrFE) by CF Activation via a Cu(0) Mediated Controlled Radical Polymerization Process.

In the present work, poly(methyl methacrylate) (PMMA) is successfully grafted onto poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) side chains via directly activated CF bonds using Cu(0)/2,2'-bipyridine as catalyst. The reaction mechanism and the initiating sites can be confirmed by the structure of the graft copolymer. The graft copolymerization exhibits first-order kinetics, and reaction conditions can affect the chemical composition of the graft copolymer, including reaction time, reaction temperature, solvents, the amount of catalyst, and monomer. The introduction of rigid PMMA side chains onto P(VDF-TrFE) can effectively tune the displacement-electric field hysteresis behaviors of P(VDF-TrFE) from normal ferroelectric to anti-ferroelectric, even linear-like dielectric, under high electric field, resulting in dramatically reduced energy loss while maintaining the discharged energy density. This work may provide an effective strategy to introduce functional groups into P(VDF-TrFE) copolymer via activation of CF bonds.

Muscle fatigue detection and treatment system driven by internet of things.

BACKGROUND: Internet of things is fast becoming the norm in everyday life, and integrating the Internet into medical treatment, which is increasing day by day, is of high utility to both clinical doctors and patients. While there are a number of different health-related problems encountered in daily life, muscle fatigue is a common problem encountered by many. METHODS: To facilitate muscle fatigue detection, a pulse width modulation (PWM) and ESP8266-based fatigue detection and recovery system is introduced in this paper to help alleviate muscle fatigue. The ESP8266 is employed as the main controller and communicator, and PWM technology is employed to achieve adaptive muscle recovery. Muscle fatigue can be detected by surface electromyography signals and monitored in real-time via a wireless network. RESULTS: With the help of the proposed system, human muscle fatigue status can be monitored in real-time, and the recovery vibration motor status can be optimized according to muscle activity state. DISCUSSION: Environmental factors had little effect on the response time and accuracy of the system, and the response time was stable between 1 and 2 s. As indicated by the consistent change of digital value, muscle fatigue was clearly diminished using this system. CONCLUSIONS: Experiments show that environmental factors have little effect on the response time and accuracy of the system. The response time is stably between 1 and 2 s, and, as indicated by the consistent change of digital value, our systems clearly diminishes muscle fatigue. Additionally, the experimental results show that the proposed system requires minimal power and is both sensitive and stable.

Using an artificial neural network to map cancer common data elements to the biomedical research integrated domain group model in a semi-automated manner.

BACKGROUND: The medical community uses a variety of data standards for both clinical and research reporting needs. ISO 11179 Common Data Elements (CDEs) represent one such standard that provides robust data point definitions. Another standard is the Biomedical Research Integrated Domain Group (BRIDG) model, which is a domain analysis model that provides a contextual framework for biomedical and clinical research data. Mapping the CDEs to the BRIDG model is important; in particular, it can facilitate mapping the CDEs to other standards. Unfortunately, manual mapping, which is the current method for creating the CDE mappings, is error-prone and time-consuming; this creates a significant barrier for researchers who utilize CDEs. METHODS: In this work, we developed a semi-automated algorithm to map CDEs to likely BRIDG classes. First, we extended and improved our previously developed artificial neural network (ANN) alignment algorithm. We then used a collection of 1284 CDEs with robust mappings to BRIDG classes as the gold standard to train and obtain the appropriate weights of six attributes in CDEs. Afterward, we calculated the similarity between a CDE and each BRIDG class. Finally, the algorithm produces a list of candidate BRIDG classes to which the CDE of interest may belong. RESULTS: For CDEs semantically similar to those used in training, a match rate of over 90% was achieved. For those partially similar, a match rate of 80% was obtained and for those with drastically different semantics, a match rate of up to 70% was achieved. DISCUSSION: Our semi-automated mapping process reduces the burden of domain experts. The weights are all significant in six attributes. Experimental results indicate that the availability of training data is more important than the semantic similarity of the testing data to the training data. We address the overfitting problem by selecting CDEs randomly and adjusting the ratio of training and verification samples. CONCLUSIONS: Experimental results on real-world use cases have proven the effectiveness and efficiency of our proposed methodology in mapping CDEs with BRIDG classes, both those CDEs seen before as well as new, unseen CDEs. In addition, it reduces the mapping burden and improves the mapping quality.

Tuning the dielectric and energy storage properties of polystyrene-based polymer dielectric by manipulating dipoles and their polarizing behavior.

Polymer dielectrics with high energy density can be realized in high-k polymers, but undesirable energy loss always occurs, especially at high electric field and elevated temperature application. By systematically comparing the dielectric and energy storage properties of poly(styrene-methyl methacrylate)s (P(St-MMA)s) with PSt and PMMA homopolymers, the positive roles of the MMA units in the improvement of their dielectric and energy storage properties are well addressed. The best electric performance, including the largest Ue of 12.2 J cm-3, η of 92%, and Eb of 530 MV m-1 at ambient temperature, was obtained in the copolymer bearing 45 mol% MMA. Considering the different types of dipoles and the generated intermolecular forces, the influence of MMA on the dielectric performances of the copolymers is well illustrated. Instead of permanent dipoles alone, the combination of isolated permanent dipoles together with induced dipoles may be promising for realizing high-k, high energy density and low loss. This conclusion helps to understand the dielectric performances of polymer dielectrics from an intermolecular force point of view and proposes a strategy for realizing high energy density but low loss under a high electric field in polymer dielectrics.

Exploring Observability of Attractor Cycles in Boolean Networks for Biomarker Detection.

Boolean Network (BN) is a simple and popular mathematical model that has attracted significant attention from systems biology due to its capacity to reveal genetic regulatory network behavior. In addition, observability, as an important network feature, plays a vital role in deciphering the underlying mechanisms driving a genetic regulatory network and has been widely investigated. Prior studies examined observability of BNs and other complex networks. That said, observability of attractor, which can serve as a biomarker for disease, has not been fully examined in the literature. In this study, we formulated a new definition for singleton or cyclic attractor observability in BNs and developed an effective methodology to resolve the captured problem. We also showed complexity is of O(Pmn), when the maximal period of cyclic attractor is P, the number of attractor is m and the number of genes is n. Importantly, we have confirmed our method can faithfully predict the expression pattern of segment polarity genes in Drosophila melanogaster and showed it can effectively and efficiently deal with the captured observability problem.

Regulating Dielectric and Ferroelectric Properties of Poly(vinylidene fluoride-trifluoroethylene) with Inner CH=CH Bonds.

Poly(vinylidene fluoride) (PVDF) based ferroelectric polymers have attracted considerable attention both academically and industrially due to their tunable ferroelectric properties. By pinning the conformation of the polymer chain and the ferroelectric phase physically or chemically, the ferroelectric behaviors of PVDF based polymers could be finely turned from normal ferroelectric into relaxor ferroelectric, anti-ferroelectric like, and even linear dielectric. Besides high energy electron irradiation and chemical copolymerization with the bulky monomers, in this work, an alternative strategy is presented to regulate the dielectric and ferroelectric performances of PVDF based ferroelectric polymer for the first time. CH=CH bonds with the desired content are inserted by a controlled dehydrofluorination reaction into a poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) copolymer (TrFE refers to trifluoroethylene) synthesized from the hydrogenation of P(VDF-CTFE) (CTFE refers to chlorothrifluoroethylene). The influence of the CH=CH bonds along with the fabrication conditions on the crystallization and ferroelectric relaxation of the resultant copolymers (referred to P(VDF-TrFE-DB)) was carefully characterized and discussed. The nonrotatable CH=CH bonds result in depressed dielectric and ferroelectric performances in the as-cast films by confining the orientation of ferroelectric grains in P(VDF-TrFE). The normal ferroelectric performance of P(VDF-TrFE) is turned into anti-ferroelectric like behavior in the resultant P(VDF-TrFE-DB). The cleavage of CH=CH bonds is responsible for the recovery of the ferroelectric behavior in the annealed samples. Uniaxial stretching favors the alignment of the polymer chain and ferroelectric domains, which may address the further regulated ferroelectric characters in the stretched samples.

Copper(0) Mediated Single Electron Transfer Controlled Radical Polymerization toward CF Bonds on Poly(vinylidene fluoride).

The first copper(0) mediated controlled radical polymerization (CRP) of methyl methacrylate (MMA) toward CF bonds onto poly(vinylidene fluoride) (PVDF) is reported with rather high activity. By avoiding the halogen exchange, Cu0 instead of CuI complexes utilized as catalyst is responsible for the significantly improved polymerization activity. Using FH decoupled nuclear magnetic resonance technique, the grafting sites onto PVDF are finely located. From this, detailed topologic information including the grafting density, average length of each side chain, along with the overall grafted content of PMMA, is detected by tracking the polymerization as a function of time. This work offers not only a facile CRP strategy based on inactive CF bonds but also a deep insight into the cleavage of F-bearing compounds in organic chemistry.

Chemical bonding-induced low dielectric loss and low conductivity in high-K poly(vinylidenefluoride-trifluorethylene)/graphene nanosheets nanocomposites.

Blending high-permittivity (εr) ceramic powders or conductive fillers into polymers to form 0-3-type composites has been regarded as one of the most promising processes to achieve high-dielectric-permittivity materials with excellent processing performance. The high dielectric loss and conductivity induced by the interface between the matrix and fillers as well as the leakage current have long been a great challenge of dielectric composites, and the resolution of these challenges is still an open question. In this work, poly(vinylidenefluoride-trifluorethylene with double bonds)/graphene nanosheets (P(VDF-TrFE-DB)/GNS) terpolymer nanocomposites were fabricated via a solution-cast process. GNSs were functionalized with KH550 to improve the dispersion in the terpolymer matrix solution and crosslinked with P(VDF-TrFE-DB) by a free-radical addition reaction in the nanocomposites. Compared with neat terpolymer, significantly increased dielectric permittivity and a low loss were observed for the composites. For instance, at 1 kHz the P(VDF-TrFE-DB)/GNS composites with 4 vol % GNS possessed a dielectric permittivity of 74, which is over seven times larger than that of neat terpolymer. However, a rather low dielectric loss (0.08 at 1 kHz) and conductivity (3.47 × 10(-7) S/m at 1 kHz) are observed in the P(VDF-TrFE-DB)/GNS composites containing up to 12 vol % GNS. The covalent bonding constructed between P(VDF-TrFE-DB) and GNS is responsible for the reduced aspect ratio of the GNS and the crystalline properties of P(VDF-TrFE-DB) as well as the improved compatibility between them. As a result, the high-dielectric-loss conductivity of polymer composites, mainly induced by conduction loss and the interface polarization between the matrix and filler, were effectively restricted. Meanwhile, the 3D network established between P(VDF-TrFE-DB) and GNS endows the P(VDF-TrFE-DB)/GNS composites at high temperature with excellent mechanical and dielectric properties. Besides preparing high-performance dielectric composites, this facile route may also be utilized to fabricate high-performance nanocomposites by inhibiting the poor compatibility between fillers and polymeric matrix.

Assessment of urban air quality in China using air pollution indices (APIs).

UNLABELLED: This study gathered and processed the available air quality daily reports in 86 cities throughout China in 2001-2011. Urban air quality was assessed in terms of the evolution of the key pollutants, the pollution level, and the PM10 (particulate matter with an aerodynamic diameter < 10 microm) concentrations. The authors conclude that PM10 is the most important pollutant in Chinese cities, especially after the national sulfur dioxide (SO2) controls during the 11th Five Year Plan (FYP; 2006-2010). A notable advance was the reduction of extremely heavily polluted days with air pollution index (API) above 150 from 7% in 2001 to 1% in 2011 in the all-city average. In addition, the average API-derived PM10 concentrations continually decreased during the past 11 yr. Additionally, the pollution pattern of "more severe from south to north "in China became less obvious due to the decline of PM10 concentrations in the northern cities and the more obvious regional characteristics of air pollution. Nevertheless, more pollutants should be included in the API system to fully reflect the air quality status and guide future air pollution controls in Chinese cities. IMPLICATIONS: Air quality daily report, the only publicly accessible observation database in the past decade, provides valuable insight into the air quality in Chinese cities. Using this data set, this paper assesses the status and change of urban air quality in China in 2001-2011, during which great effort was made to mitigate urban air pollution. It is valuable for the further refinement of national air quality control strategies, and the needs of updating the present daily report system are implicated.

Controlled hydrogenation of P(VDF-co-CTFE) to prepare P(VDF-co-TrFE-co-CTFE) in the presence of CuX (X = Cl, Br) complexes.

An environmentally friendly and controllable P(VDF-co-CTFE) hydrogenation route involving the transition-metal complex mediated radical chain transfer reaction is successfully developed to synthesize P(VDF-co-CTFE-co-TrFE). The typical transition metal catalysts of ATRP reaction could be applied in this process.