bluuebunny/crossref_metadata_2025 huggingface dataset:
Information-based massive data retrieval method based on distributed decision tree algorithm
Authors: Chen Bin , Chen Qingming , Ye Peishan
Published: June 2022

Based on the distributed decision tree algorithm, this paper first proposes a method of vertically partitioning datasets and synchronously updating the hash table to establish an information-based mass data retrieval method in a heterogeneous distributed environment, as well as using interval segmentation and interval filtering technologies for improved algorithm of distributed decision tree. The distributed decision tree algorithm uses the attribute histogram data structure to merge the category list into each attribute list, reducing the amount of data that needs to reside in the memory. Second, we adopt the strategy of vertically dividing the dataset and synchronously updating the hash table, select the hash table entries that can be used to update according to the minimum Gini value, modify the corresponding entries and use the hash table to record and control each sub-site. In the case of node splitting, it has a high accuracy rate. In addition, for classification problems that meet monotonic constraints in a distributed environment, this paper will extend the idea of building a monotonic decision tree in a distributed environment, supplementing the distributed decision tree algorithm, adding a modification rule and modifying the generated nonmonotonic decision tree to monotonicity. In order to solve the high load problem of the privacy-protected data stream classification mining algorithm under a single node, a Storm platform for the parallel algorithm PPFDT_P based on the distributed decision tree algorithm is designed and implemented. At the same time, considering that the word vector model improves the deep representation of features and solves the problem of feature high-dimensional sparseness, and the iterative decision tree algorithm GBDT model is more suitable for non-high-dimensional dense features, the iterative decision tree algorithm will be integrated into the word vector model (GBDT) in the data retrieval application, using the distributed representation of words, namely word vectors, to classify short messages on the GBDT model. Experimental results show that the distributed decision tree algorithm has high efficiency, good speed-up and good scalability, so that there is no need to increase the number of datasets at each sub-site at any time. Only a small number of data items are inserted. By splitting some leaf nodes, a small amount is added by branching to achieve a monotonic decision tree. The proposed system achieves a massive data ratio of 54.1% while compared with other networks of massive data ratio.
Concerns on Medications Used in Osteoporosis
Authors: Li-Yu Julie
Published: June 2022

Osteoporosis is a systemic skeletal disorder that affects bone microarchitecture resulting to fragility fractures. Randomized controlled trials have shown efficacy of antiresorptives and osteoanabolic agents in addressing concerns of osteoporosis especially in the older population. However, published guidance from several organizations started to focus as well on the perceived harms most especially of bisphosphonates considering their persistent effect on the bones. Similar to other chronic diseases, decision on whether or not to continue therapy depends on factors that might persistently provide signal on the individual’s further risk of unwanted but preventable outcomes.
Hip Fracture in Asia with a Special Focus in the Oldest Old: A Brief Review
Authors: Cheung Ching-Lung , Ho Shun-Cheong , Krishnamoorthy Suhas , Zhang Xiaowen
Published: June 2022

Osteoporosis is a prevalent disease globally, with fragility fracture being the clinical outcome. Hip fracture is mostly associated with morbidity, immobility, and mortality among all fragility fractures. Although earlier studies in the 1990s projected that half of the hip fractures in the world will occur in Asia by 2050, epidemiology studies in Asia are inadequate. On the other hand, although the stabilizing or reducing trend of hip fracture incidence was reported in some countries or regions, the total number of hip fractures may still increase due to the rapid increase of the oldest old population. The oldest old usually have the highest fracture incidence, while the available treatment and management of osteoporosis for them are suboptimal. The undertreatment could be due to the “unfavorable” risk–benefit profile, lack of fracture prediction tool for the oldest old, and the presence of multiple comorbidities. A strategic management plan for osteoporosis in the oldest old can help cope with the coming “fracture tsunami” and achieve the “healthy aging” goal among the oldest old. Here, we reviewed the recent Asian epidemiology studies on hip fracture, focusing on the current treatment, fracture prediction, and comorbidities of the oldest old.
Edge Computing for Cyber-physical Systems: A Systematic Mapping Study Emphasizing Trustworthiness
Authors: Sánchez José Manuel Gaspar , Jörgensen Nils , Törngren Martin , Inam Rafia , Berezovskyi Andrii , Feng Lei , Fersman Elena , Ramli Muhammad Rusyadi , Tan Kaige
Published: June 2022

Edge computing is projected to have profound implications in the coming decades, proposed to provide solutions for applications such as augmented reality, predictive functionalities, and collaborative Cyber-Physical Systems (CPS). For such applications, edge computing addresses the new computational needs, as well as privacy, availability, and real-time constraints, by providing local high-performance computing capabilities to deal with the limitations and constraints of cloud and embedded systems. Edge computing is today driven by strong market forces stemming from IT/cloud, telecom, and networking—with corresponding multiple interpretations of “edge computing” (e.g., device edge, network edge, distributed cloud). Considering the strong drivers for edge computing and the relative novelty of the field, it becomes important to understand the specific requirements and characteristics of edge-based CPS, and to ensure that research is guided adequately, e.g., avoiding specific gaps.

Our interests lie in the applications of edge computing as part of CPS, where several properties (or attributes) of trustworthiness, including safety, security, and predictability/availability, are of particular concern, each facing challenges for the introduction of edge-based CPS. We present the results of a systematic mapping study, a kind of systematic literature survey, investigating the use of edge computing for CPS with a special emphasis on trustworthiness. The main contributions of this study are a detailed description of the current research efforts in edge-based CPS and the identification and discussion of trends and research gaps. The results show that the main body of research in edge-based CPS only to a very limited extent consider key attributes of system trustworthiness, despite many efforts referring to critical CPS and applications like intelligent transportation. More research and industrial efforts will be needed on aspects of trustworthiness of future edge-based CPS including their experimental evaluation. Such research needs to consider the multiple interrelated attributes of trustworthiness including safety, security, and predictability, and new methodologies and architectures to address them. It is further important to provide bridges and collaboration between edge computing and CPS disciplines.
Diffusion of Legal Innovations
Authors: Engel Christoph , Weinshall Keren
Published: June 2022

The law is permanently under construction. Most legal change is intentional. A legislator, a court, or one of the law's subjects hopes to better achieve a purpose by switching from one rule, one interpretation, or one remedy to the next. Yet empirically, legal innovation tends to be a process that takes time. At the macro level, the diffusion path is often S shaped: It does not start immediately and levels off after a while. This article links legal innovation to diffusion research and discusses micro processes that have the potential to generate the observed diffusion paths.
High-Efficient Water Splitting Using Nanostructured Conical GaN
Authors: Hu Tiangui , Liu Chang , Liu Jian
Published: June 2022

Nanostructured GaN has many advantages in water splitting, such as stronger light absorption, shorter migration distance and more reactive sites. Here, we have introduced a conical nanostructured GaN with the significant improvement of water splitting performance. The fabrication method is simple without any extra mask, including electrochemical etching and ICP etching only, which largely reduces the complexity and cost for fabricating nanostructured GaN. By making use of the large number of pores formed in electrochemical etching, a conical GaN nanostructure can be prepared using ICP etching afterwards. Compared with the control planar GaN, the reflectivity of the conical GaN decreases by ∼2.57 times, indicating the light absorption of the conical GaN increases significantly. The corresponding water splitting current density of the conical GaN has also been measured, which is 0.69 mA cm−2 at 1 V, ∼6.27 times higher than that of control planar GaN (0.11 mA cm−2). Our work provides a simple method to fabricate high-performance nanostructured GaN, and broadens the application of III-nitrides for efficient energy storage and conversion.
Conducting Polymer Hydrogel Driven By Sodium Chloride as High Performance Flexible Supercapacitor Electrode
Authors: Ye Shi-Fang , Zhu Ke-Hu , Ma Wen-bin , Dou Li-Yang , Cui Pei-Xin , Sha Heng , Han Xiao-dong , Wei Xian-yong , Tao Xue-Yu
Published: June 2022

With the rapid development of the wearable devices and flexible supercapacitors (FSCs), urgent demand for electrodes with high specific capacitance and excellent flexibility have been put forward. Herein, a self-standing conducting polymer hydrogel electrode has been successfully synthesized by in situ polymerization of aniline (ANI) in aqueous solution of polyvinyl alcohol (PVA), phytic acid (PA) and sodium chloride (NaCl). The prepared PANI/PVA/NaCl (PPN) hydrogel electrode shows high specific capacitance (1544 mF cm−2 at current density of 1 mA cm−2), good flexibility (elongation at fracture of 110%), satisfactory electrochemical stability (92% capacitance retention after 500 repeated bending cycles) and excellent cycling stability (78.2% capacitance retention after 10000 cycles) due to the uniform 3D interconnected structure driven by NaCl pseudo template. In order to further explore the potential application prospects of the synthesized hydrogel in flexible devices, a series of all-hydrogel-state FSCs are assembled based on the prepared PPN hydrogel electrodes and typical PVA/H2SO4 electrolyte. The assembled FSCs exhibit high energy density of 51.1 μWh cm−2 at power density of 250 μW cm−2 and long-life stability of 81.10% capacitance retention after 10000 charge/discharge cycles. This work provides a new synthesis strategy for the high performance energy storage electrodes and devices.
Hydrogen-powered Electrochemically-driven CO2 Removal from Air Containing 400 to 5000 ppm CO2
Authors: Matz Stephanie , Shi Lin , Zhao Yun , Gottesfeld Shimshon , Setzler Brian P. , Yan Yushan
Published: June 2022

The performance of a hydrogen-powered, electrochemically-driven CO2 separator (EDCS) was demonstrated at cathode inlet CO2 concentrations from 400 ppm to 5,000 ppm. The impact of current density and CO2 concentration were evaluated to predict operating windows for various applications. The single-cell data was used to scale a 100 cm2, multi-cell stack using a shorted-membrane design for four applications: direct air capture (DAC), hydroxide exchange membrane fuel cell (HEMFC) air pretreatment, submarine life support, and space habitation. For DAC, a 339-cell EDCS stack (7.7 L, 17 kg) was projected to remove 1 tonne CO2 per year. The addition of the EDCS in HEMFC systems would result in nearly a 30% increase in volume, and therefore further improvements in performance would be necessary. A module containing five 338-cell EDCS stacks (38 L, 85 kg) in parallel can support a 150 person crew at 2.1% of the volume of the liquid amine system employed in submarines. For space habitation, a 109-cell EDCS stack (3.2 L, 10 kg) is adequate for 6 crewmembers, and is less than 1% the size and 5% the weight of the current CO2 removal system installed on the International Space Station.
One-pot Preparation of CoS/CuS Nanocomposite-sensitized TiO2 Nanorod Arrays with Enhanced Photoelectrochemical Performance
Authors: Yin Zhuangzhuang , Qi Shihan , Deng Shangkun , Guo Jun , Gan Wei , Chen Peng , Ding Chunsheng , Li Ziliang , Li Jianrou , Lu Yuqing , Zhao Ziwei , Ling Qi , Zhang Miao , Sun Zhaoqi
Published: June 2022

Transition metal sulfides are widely used for the modification of TiO2 to improve its light absorption range due to their small bandgaps. In this work, novel CoS/CuS/TiO2 was synthesized via a simple one-pot hydrothermal preparation method. Using various characterization techniques, CoS/CuS/TiO2 was found to demonstrate excellent photoelectrochemical performance and photocatalytic activity for the degradation of tetracycline hydrochloride. The CoS/CuS/TiO2 catalyst showcased a maximum photocurrent density of 55 μA cm−2, which was 7.8 times higher than that of unmodified TiO2 nanorods. Under visible light irradiation using Xe lamp, the photocatalytic degradation efficiency of CoS/CuS/TiO2 on tetracycline hydrochloride was found to be significantly improved, where it recorded an excellent degradation rate of 64.0% at 90 min. The charge transfer mechanism of the proposed material was also investigated.
[Retracted] Kukoamine A Improves Mycoplasma pneumoniae Pneumonia by Regulating miR‐222‐3p/Superoxide Dismutase 2
Authors: Liu Xiu-Xiu , Wang Ming-Jing , Kan Qian-Na , Li Cui , Xiao Zhen , Jiang Yong-Hong , Li Wen , Li Xiao , Jiang Zhi-Yan
Published: June 2022

Mycoplasma pneumoniae pneumonia (MPP) represents a common respiratory disease in children patients. Kukoamine A (KuA) is a spermine alkaloid found in the Chinese herb Cortex Lycii radices, which has a variety of pharmacological properties. However, no study has been reported on the role of KuA in MPP. Exosomes, a type of lipid bilayer‐enclosed extracellular vesicles, can be delivered to the target cells, where they regulate function and physiology. With the use of human alveolar basal epithelial cells (HABECs) as an in vitro model, in this study, we sought to characterize the changes in levels of superoxide dismutase 2 (SOD2) and proinflammatory cytokines including IL‐6 and TNF‐α in HABECs in response to exosomes, which were isolated from peripheral blood serum of MPP patients. We found that, compared to normal, MPP patients exhibited a significant up‐regulated miR‐222‐3p. Further, exosomal miR‐222‐3p downregulated SOD2 activity but promoted nuclear NF‐κB activity and expression of IL‐6 and TNF‐α in HABECs, ultimately leading to an oxidative stress condition. Interestingly, such stimulating effects were attenuated by the pretreatment of KuA. This study suggests a critical role possessed by KuA in MPP by regulating the miR‐222‐3p/SOD2 axis, which represents a promising strategy for the treatment of MPP.
High Sucrose Ingestion during a Critical Period of Vessel Development Promotes the Synthetic Phenotype of Vascular Smooth Muscle Cells and Modifies Vascular Contractility Leading to Hypertension in Adult Rats
Authors: Castrejón-Téllez Vicente , Rubio-Ruiz María Esther , Cano-Martínez Agustina , Pérez-Torres Israel , Del Valle-Mondragón Leonardo , Carreón-Torres Elizabeth , Guarner-Lans Verónica
Published: June 2022

Cardiometabolic diseases, including hypertension, may result from exposure to high sugar diets during critical periods of development. Here, we studied the effect of sucrose ingestion during a critical period (CP) between postnatal days 12 and 28 of the rat on blood pressure, aortic histology, vascular smooth muscle phenotype, expression of metalloproteinases 2 and 9, and vascular contractility in adult rats and compared it with those of adult rats that received sucrose for 6 months and developed metabolic syndrome (MS). Blood pressure increased to a similar level in CP and MS rats. The diameter of lumen, media, and adventitia of aortas from CP rats was decreased. Muscle fibers were discontinuous. There was a decrease in the expression of alpha-actin in CP and MS rat aortas, suggesting a change to the secretory phenotype in vascular smooth muscle. Metalloproteinases 2 and 9 were decreased in CP and MS rats, suggesting that phenotype remains in an altered steady stationary state with little interchange of the vessel matrix. Aortic contraction to norepinephrine did not change, but aortic relaxation was diminished in CP and MS aortas. In conclusion, high sugar diets during the CP increase predisposition to hypertension in adults.
Human Psychological Disorder towards Cryptography: True Random Number Generator from EEG of Schizophrenics and Its Application in Block Encryption’s Substitution Box
Authors: Khan Muhammad Fahad , Saleem Khalid , Hazzazi Mohammad Mazyad , Alotaibi Mohammed , Shukla Piyush Kumar , Aqeel Muhammad , Tuncer Seda Arslan
Published: June 2022

Schizophrenia is a multifaceted chronic psychiatric disorder that affects the way a human thinks, feels, and behaves. Inevitably, natural randomness exists in the psychological perception of schizophrenic patients, which is our primary source of inspiration for this research because true randomness is the indubitably ultimate valuable resource for symmetric cryptography. Famous information theorist Claude Shannon gave two desirable properties that a strong encryption algorithm should have, which are confusion and diffusion in his fundamental article on the theoretical foundations of cryptography. Block encryption strength against various cryptanalysis attacks is purely dependent on its confusion property, which is gained through the confusion component. In the literature, chaos and algebraic techniques are extensively used to design the confusion component. Chaos- and algebraic-based techniques provide favorable features for the design of the confusion component; however, researchers have also identified potential attacks on these techniques. Instead of existing schemes, we introduce a novel methodology to construct cryptographic confusion component from the natural randomness, which are existing in the psychological perception of the schizophrenic patients, and as a result, cryptanalysis of chaos and algebraic techniques are not applicable on our proposed technique. The psychological perception of the brain regions was captured through the electroencephalogram (EEG) readings during the sensory task. The proposed design passed all the standard evaluation criteria and validation tests of the confusion component and the random number generators. One million true random bits are assessed through the NIST statistical test suite, and the results proved that the psychological perception of schizophrenic patients is a good source of true randomness. Furthermore, the proposed confusion component attains better or equal cryptographic strength as compared to state-of-the-art techniques (2020 to 2021). To the best of our knowledge, this nature of research is performed for the first time, in which psychiatric disorder is utilized for the design of information security primitive. This research opens up new avenues in cryptographic primitive design through the fusion of computing, neuroscience, and mathematics.
Exercise Improves Spatial Learning and Memory Performance through the Central GLP-1 Receptors
Authors: Taati Majid , Barzegar Peyman Esmaeili Fard , Raisi Abbas
Published: June 2022

The glucagon-like peptide 1 (GLP-1) is a hormone which is produced in the enteroendocrine L-cells in the ileum and the neurons of nucleus tractus solitarius (NTS) in the brain which has numerous metabolic effects. The central GLP-1R’s role in cognitive functioning is well known. On the contrary, it has been shown that exercise has positive effects on brain function. So, we decided to elucidate whether the central GLP-1 has a role in memory and learning. Thirty-two rats were used in this experiment in 4 groups. After anesthetizing the rats, the right lateral ventricle was detected, and a cannula was directed to the ventricle. Ten micrograms of exendin-3 or sterile saline, according to the group, was injected via ICV once daily for seven days. The rats in the exercise group considered an exercise period of one hour each day (17 meters per minute) for seven consecutive days. To evaluate the performance of memory and learning, a standard Morris water maze (MWM) tank was utilized. According to the results, the TE-exendin group showed a statistically significant difference from the TE-SAL group in both parameters of latency and time in the zone. In summary, memory and learning were improved by GLP-1R in the exercise group, but not in the sedentary group, which we can hypothesize that exercise can affect memory and learning through this pathway.
[Retracted] Application of Dynamic Contrast‐Enhanced MRI in the Diagnosis of Rheumatoid Arthritis
Authors: Zhang Bin , Xiao Li , Zhou Hui , Li Ming , Wang Jingming , Guo Lina
Published: June 2022

In order to solve the application problem of dynamic contrast‐enhanced MRI in the diagnosis of rheumatoid arthritis, this paper proposes application research based on dynamic contrast‐enhanced MRI in the staging diagnosis of rheumatoid arthritis. Dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) has a high value in evaluating the activity of patients with early rheumatoid arthritis (RA). This paper discusses the correlation between hemodynamic parameters and omeractramris score, clinical laboratory indexes, and activity score (DAS28), analyzes its feasibility in evaluating the prognosis of RA, and provides a reliable basis for the rational formulation of an early RA treatment plan. After reviewing the previous cases, 33 patients with subclinical synovitis of RA were selected for wrist joint contrast‐enhanced ultrasonography. The data were analyzed by contrast‐enhanced software, and the quantitative parameters of contrast‐enhanced were obtained: start development time (AT), peak time (TTP), peak intensity (PI), grad gradient, and area under the curve (AUC). The synovial blood supply was classified by CEUS, and the CEUS blood supply classification and power Doppler (PDUS) blood supply classification were compared. The results of regression analysis showed that AUC (or = 1.026, 95% CI: 1.001–1.052) and PI (or = 1.561, 95% CI: 1.019–2.393) were independent risk factors for predicting the aggravation of the disease. The diagnostic efficacy of AUC and PI in predicting the aggravation of the disease was analyzed. The areas under the ROC curve of AUC and PI were 0.935 and 0.927, respectively, and the difference between them was not statistically significant.
An Improved Knothe Time Function Model in the Prediction of Ground Mining Subsidence by Using the Kalman Filter Method
Authors: Zhang Shifang , Zhang Jin
Published: June 2022

The Knothe time function is a classical method in predicting the ground mining subsidence. Nevertheless, it does not take the observation data into account in the prediction process. The Kalman filter method can solve this issue at large extent. Taking a coal mining work face of Xishan Coalfield as an example, this research compares the performance of the traditional Knothe time function and that of the improved Knothe time function by using the Kalman filter method. The comparison results show that through an improvement by using the Kalman filter method, the RMSE is improved from 133.4 mm to 78.3 mm; ME, from 91.9 mm to 3.1 mm; and the relative error, from 8.1% to 5.7%. Meanwhile, the improved model has good astringency. These verify that the improved model has higher accuracy and reliability. Hence, this research presents an effective method in predicting ground subsidence of mining area by improving the Knothe time function using the Kalman filter method.
Music Emotion Classification Method Based on Deep Learning and Explicit Sparse Attention Network
Authors: Jia Xiaoguang
Published: June 2022

In order to improve the accuracy of music emotion recognition and classification, this study combines an explicit sparse attention network with deep learning and proposes an effective emotion recognition and classification method for complex music data sets. First, the method uses fine-grained segmentation and other methods to preprocess the sample data set, so as to provide a high-quality input data sample set for the classification model. The explicit sparse attention network is introduced into the deep learning network to reduce the influence of irrelevant information on the recognition results and improve the emotion classification and recognition ability of music sample data set. The simulation experiment is based on the actual data set of the network. The experimental results show that the recognition accuracy of the proposed method is 0.71 for happy emotions and 0.688 for sad emotions. It has a good ability of music emotion recognition and classification.
Evaluating Agile Practices in Green Supply Chain Management Using a Fuzzy Multicriteria Approach
Authors: Dolatabad Mahsa Jamshidi , Azhdarifard Mahsa , Acwin Dwijendra Ngakan Ketut , Ali Sharhan Al-Sudani Ahmed Qassem
Published: June 2022

Ensuring the successful implementation of sustainable development goals in each country today depends heavily on the preservation and optimal use of its limited irreplaceable resources; therefore, a wide range of measures have been thus far taken by governments to deal with this issue. The study’s main aim is to evaluate agile practices in green supply chain management utilizing a fuzzy multicriteria approach. To meet that aim, a quantitative research design was carried out by collecting data from fieldwork in the form of completing a questionnaire. Based on the results, the global spread of environmental standards along with the growing consumer demand for integrating green product supply into supply chain management (SCM), encompassing all practices associated with the flow of goods from the extraction and use of raw materials to delivery to end consumers as well as the flow of information throughout this chain, has accordingly given rise to the novel concept of green supply chain management (GSCM). Finally, GSCM criteria were identified and then prioritized, exploiting a fuzzy multicriteria approach in the present study.
The Effectiveness and Safety of Ropivacaine and Medium-Dose Dexmedetomidine in Cesarean Section
Authors: Huang Bin-Bin , Niu Shi-Kun
Published: June 2022

Objective: To study the effects of epidural anesthesia with different doses of dexmedetomidine and ropivacaine on postoperative hemodynamics and neonatal outcome of cesarean section parturients. Methods. A total of 90 parturients who underwent cesarean section admitted to our hospital from January 2019 to January 2020 were selected as the research objects and were divided into groups A, B, and C according to different dosages of dexmedetomidine, with 30 cases in each group. Groups A, B, and C were given dexmedetomidine 0.5 μg/kg, 0.8 μg/kg, 1.0 μg/kg, respectively, combined with 0.2% ropivacaine. The anesthesia effect, traction response, hemodynamic indexes, and neonatal Apgar score of the three groups were compared; the “Numerical Rating Scale (NRS) Score” was used to assess the postoperative pain of the parturients, and the “Ramsay Sedation Scale” was used to assess the sedation state of the parturients. Results. The superior anesthesia effect of group B was obtained compared with groups A and C (

P
<
0.05

). Group B witnessed a lower degree of grade III stretching response, as compared to group A (

P
<
0.05

). In comparison with groups A and C, superior results of the heart rate and mean artery pressure (MAP) of group B at T1 and T2 were obtained (

P
<
0.05

). The neonatal Apgar score in group B was lower than those in groups A and C (

P
<
0.05

), and the NRS score of group B was also lower than that of group A (

P
<
0.05

). Compared with groups A and C, group B yielded a more favorable outcome in terms of the Ramsay score (

P
<
0.05

). Conclusion. The use of medium-dose dexmedetomidine in cesarean section parturients is safer and can effectively reduce the impact on maternal hemodynamics, which is worthy of promotion and application.
In Vivo Functional Assessment of Sodium-Glucose Cotransporters (SGLTs) Using [18F]Me4FDG PET in Rats
Authors: Matsusaka Yohji , Chen Xinyu , Arias-Loza Paula , Werner Rudolf A. , Nose Naoko , Sasaki Takanori , Rowe Steven P. , Pomper Martin G. , Lapa Constantin , Higuchi Takahiro
Published: June 2022

Background. Mediating glucose absorption in the small intestine and renal clearance, sodium glucose cotransporters (SGLTs) have emerged as an attractive therapeutic target in diabetic patients. A substantial fraction of patients, however, only achieve inadequate glycemic control. Thus, we aimed to assess the potential of the SGLT-targeting PET radiotracer alpha-methyl-4-deoxy-4-[18F]fluoro-D-glucopyranoside ([18F]Me4FDG) as a noninvasive intestinal and renal biomarker of SGLT-mediated glucose transport. Methods. We investigated healthy rats using a dedicated small animal PET system. Dynamic imaging was conducted after administration of the reference radiotracer 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG), or the SGLT-targeting agent, [18F]Me4FDG either directly into the digestive tract (for assessing intestinal absorption) or via the tail vein (for evaluating kidney excretion). To confirm the specificity of [18F]Me4FDG and responsiveness to treatment, a subset of animals was also pretreated with the SGLT inhibitor phlorizin. In this regard, an intraintestinal route of administration was used to assess tracer absorption in the digestive tract, while for renal assessment, phlorizin was injected intravenously (IV). Results. Serving as reference, intestinal administration of [18F]FDG led to slow absorption with retention of [Formula: see text]% of administered radioactivity at 15 min. [18F]Me4FDG, however, was rapidly absorbed into the blood and cleared from the intestine within 15 min, leading to markedly lower tracer retention of [Formula: see text]% ([Formula: see text]). Intraintestinal phlorizin led to marked increase of [18F]Me4FDG uptake (15 min, [Formula: see text]%; [Formula: see text] vs. untreated controls), supporting the notion that this PET agent can measure adequate SGLT inhibition in the digestive tract. In the kidneys, radiotracer was also sensitive to SGLT inhibition. After IV injection, [18F]Me4FDG reabsorption in the renal cortex was significantly suppressed by phlorizin when compared to untreated animals (%ID/g at 60 min, [Formula: see text] vs. untreated controls, [Formula: see text]; [Formula: see text]). Conclusion. As a noninvasive read-out of the concurrent SGLT expression in both the digestive tract and the renal cortex, [18F]Me4FDG PET may serve as a surrogate marker for treatment response to SGLT inhibition. As such, [18F]Me4FDG may enable improvement in glycemic control in diabetes by PET-based monitoring strategies.
Effect of Physical Exercise Intervention Based on Improved Neural Network on College Students’ Mental Health
Authors: Cai Linlin
Published: June 2022

Physical exercise refers to various physical exercises carried out through certain means and methods. Physical exercise can not only achieve the purpose of strengthening the body and health but also make people face challenges in physical and mental sports, and the resulting psychological satisfaction and excitement make exercisers happy physically and mentally. Physical activity has a certain appeal that makes it one of the most effective ways for modern people to alleviate mental illnesses. The human brain’s reaction time is linked to its thinking speed and intelligence. Regular physical activity can increase human brain cell reaction time and completely utilize human brain capacity, which is beneficial to the healthy development of human attention, memory, imagination, and thinking ability. Scientific and reasonable physical exercise is also an important means to improve people’s intelligence levels. Everyone’s physical health level is closely related to their mental health. A healthy mind comes from a healthy body. A large number of scientific studies have confirmed that reasonably arranging the contents and methods of physical exercise according to their own health level and psychological state cannot only enhance the physique of college students but also cultivate their excellent personality. Firstly, this paper summarizes the influence of physical exercise on mental health. The ways of employing physical exercise to improve and improve the mental health of college students are presented in this study. Then, this paper proposes a physical exercise intervention based on an improved neural network (NN), which has an impact on the mental health level of college students, and the effectiveness of this model is verified by simulation experiments.
Integrated Bioinformatic Analysis of DNA Methylation and Immune Infiltration in Endometrial Cancer
Authors: Dai Fangfang , Wu Jinglin , Deng Zhimin , Li Hengxing , Tan Wei , Yuan Mengqin , Yang Dongyong , Liu Shiyi , Zheng Yajing , Hu Min , Yuan Chaoyan , Cheng Yanxiang
Published: June 2022

Background. Endometrial cancer greatly threatens the health of female. Emerging evidences have demonstrated that DNA methylation and immune infiltration are involved in the occurrence and development of endometrial cancer. However, the mechanism and prognostic biomarkers of endometrial cancer are still unclear. In this study, we assess DNA methylation and immune infiltration via bioinformatic analysis. Methods. The latest RNA‐Seq, DNA methylation data, and clinical data related to endometrial cancer were downloaded from the UCSC Xena dataset. The methylation‐driven genes were selected, and then the risk score was obtained using “MethylMix” and “corrplot” R packages. The connection between methylated genes and the expression of screened driven genes were explored using “survminer” and “beeswarm” packages, respectively. Finally, the role of VTCN1in immune infiltration was analyzed using “CIBERSORT” package. Results. In this study, 179 upregulated genes, and 311 downregulated genes were identified and found to be related to extracellular matrix organization, cell–cell junctions, and cell adhesion molecular binding. The methylation‐driven gene VTCN1 was selected, and patients classified to the hypomethylation and high expression group displayed poor prognosis. The VTCN1 gene exhibited highest correlation coefficient between methylation and expression. More importantly, the hypomethylation of promoter of VTCN1 led to its high expression, thereby induce tumor development by inhibiting CD8+ T cell infiltration. Conclusions. Overall, our study was the first to reveal the mechanism of endometrial cancer by assessing DNA methylation and immune infiltration via integrated bioinformatic analysis. In addition, we found a pivotal prognostic biomarker for the disease. Our study provides potential targets for the diagnosis and prognosis of endometrial cancer in the future.
DNA Barcoding and Phylogeny of Acari Species Based on ITS and COI Markers
Authors: Pérez-Sayas Consuelo , Pina Tatiana , Sabater-Muñoz Beatriz , Gómez-Martínez María Antonia , Jaques Josep A. , Hurtado-Ruiz Mónica A.
Published: June 2022

Acari harbor numerous minute species of agricultural economic importance, mainly Tetranychidae and Phytoseiidae. Great efforts have been established by means of recovering morphological, molecular, and phylogenetic traits for species identification. Traditional identification still relies on external diagnostic characters, which are limited and usually exhibit large phenotypic plasticity within the species, rendering them useless for species delimitation and identification. We decided to increase the number of sequences of the Acari mitochondrial COI (Cytochrome C oxidase I) marker and ITS nuclear ribosomal DNA region for species identification in Tetranychidae and Phytoseiidae. The molecular data allow us to establish species boundaries and phylogenetic relationships among several clades of Acari, mainly Tetranychidae and Phytoseiidae. Sequence comparisons between complete COI and the Acari mitochondrial COI, ITS1-5,8S-ITS2, and ITS2 among all Acari sequences have demonstrated that the selected regions, even small, gave enough informative positions for both species’ identification and phylogenetic studies. Analyses of both DNA regions have unveiled their use as species identification characters, with special emphasis on Acari mitochondrial COI for Tetranychidae and Phytoseiidae species in comparison with the Folmer fragment, which has been universally used as a barcode marker. We demonstrated that the Acari mitochondrial COI region is also a suitable marker to establish a barcode dataset for Acari identification. Our phylogenetic analyses are congruent with other recent works, showing that Acari is a monophyletic group, of which Astigmata, Ixodida, Mesostigmata, Oribatida, and Prostigmata are also monophyletic.
High Neutrophil-to-Platelet Ratio Is Associated with Poor Survival in Patients with Acute Aortic Dissection
Authors: Pang Jungang , Liu Jun , Liang Wantian , Yang Lijun , Wu Liangyin
Published: June 2022

Background. Acute aortic dissection (AAD), a serious and fatal cardiovascular disease, is characterized by inflammation that may further aggravate the condition. We evaluated the value of the neutrophil-to-platelet ratio (NPR) in the prognosis of AAD. Methods. We collected records of patients with AAD and clinical data from 2010 to 2020 and followed up on the relevant information for 136 months. The Kaplan–Meier (K–M) survival along with the univariate and multivariate Cox analyses was used to examine the prognostic value of NPR in AAD. In addition, nomograms were constructed by combining NPR, age, Stanford typing, and treatment methods. The accuracy of nomograms was evaluated using calibration plots, and the prediction efficiency of nomograms was evaluated by receiver operating characteristic curve analysis and decision curve analysis (DCA). Results. The K–M analysis showed that AAD patients with higher NPR exhibited worse prognosis. In addition, different Stanford typing and treatment methods produced varied prognosis results. Univariate and multivariate Cox analyses showed that NPR value, age, classification, and treatment were independent prognostic factors for the overall survival time of patients with AAD. Nomograms constructed by combining NPR, age, Stanford typing, and treatment methods showed good predictive efficacy, and the AUC values for 1-, 3-, and 5-year predicting were 0.82, 0.79, and 0.74, respectively. Conclusions. Our results suggest that pretreatment NPR can be used as a potential prognostic marker of overall survival time in patients with AAD.
Detection and Application of Wearable Devices Based on Internet of Things in Human Physical Health
Authors: Lou Jingjing , Yang Fan , Lv Changsheng
Published: June 2022

In order to improve the detection function of wearable intelligent devices in the Internet of things and facilitate people to control a variety of information such as heart rate, exercise state, blood oxygen saturation, and so on, the scientific detection of human physical health based on wearable devices based on Internet of things technology is proposed. Through the combination of software- and hardware-related functional modules, the real-time detection of human physical health information can be effectively realized. Firstly, the detection principle of optical capacitance product pulse wave signal and the waveform characteristics of pulse wave are introduced, and then the application scenarios and advantages of wearable devices are further introduced; then, the convolutional neural network for pulse wave signal denoising and the basic principle of self-encoder are introduced; finally, the regression prediction method and support vector machine method for pulse wave signal feature extraction are introduced in detail. The pulse wave based on optical capacitance product is removed to improve the waveform quality of pulse wave signal. Firstly, the system software development environment is briefly described. Then, the software design of watch terminal master device based on MSP432 and belt terminal slave device based on MSP430 are described in detail, and the detailed program implementation flow of each key technology in the system is given. In addition, the fall detection algorithm based on threshold discrimination is studied, and the program implementation of the algorithm is also described in detail. Finally, the system is tested. The results show that normal state mainly include normal walking, jogging, and fast sitting, and the accuracy rate is 97%, 95%, and 93%, respectively. For fall state, the experimenter needs to simulate various possible fall states, and the accuracy rate is 95%, 93%, and 95%, respectively, which verifies the detection accuracy of the algorithm. The system can automatically turn on the satellite positioning function when the user’s physical sign parameters are abnormal or the user’s current fall dangerous situation occurs, and send the current position information and alarm content information through the GSM module, so that the dangerous situation can be found and handled at the first time.
Multisensor-Based Heavy Machine Faulty Identification Using Sparse Autoencoder-Based Feature Fusion and Deep Belief Network-Based Ensemble Learning
Authors: Zhou Yiqing , Wang Jian , Wang Zeru
Published: June 2022

Faulty identification plays a vital role in the area of prognostic and the health management (PHM) of the industrial equipment which offers great support to the maintenance strategy decision. Owing to the complexity of the machine internal component-system structure, the precise prediction of the heavy machine is hard to be obtained, thus full of uncertainty. Moreover, even for a single component, the feature representation of the acquired conditional monitoring signal can be different due to the different deployment of the sensor location and environmental inference, causing difficulty in feature selection and uncertainty in faulty identification. In order to improve the model identification reliability, a novel hybrid machine faulty identification approach based on sparse autoencoder- (SAE-) and deep belief network- (DBN-) based ensemble learning is proposed in this paper. First, six kinds of statistical features are extracted and normalized from multiple sensors monitoring the same target component. Second, the six extracted features are fused by the two-stage SAE proposed in this paper from the sensor dimension and feature dimension, respectively. The composite feature fused in the feature dimension is regarded as the comprehensive representation of the corresponding component. Finally, the fused features containing comprehensive representation of different components are utilized to predict the machine health condition by the ensemble of multiple deep belief classifiers. The effectiveness of the proposed method is validated by the two case studies of wind turbine gearbox and industrial port crane. The experimental result shows that the proposed ensemble learning approach outperforms other traditional deep learning approaches in terms of the prediction accuracy and the prediction stability when dealing with multisensor feature fusion and the precise faulty identification of the industrial heavy machine.
The Landscape of Using Glycosyltransferase Gene Signatures for Overall Survival Prediction in Hepatocellular Carcinoma
Authors: Cai Qiang , Yu Shizhe , Zhao Jian , Ma Duo , Jiang Long , Zhang Xinyi , Yu Zhiyong
Published: June 2022

Hepatocellular carcinoma (HCC) is a heterogeneous disease that occurs in the setting of chronic liver diseases. The role of glycosyltransferase (GT) genes has recently been the focus of research associated with tumor development. However, the prognostic value of GT genes in HCC remains unclear. Therefore, this study aimed to identify GT genes related to HCC prognosis through bioinformatics analysis. We firstly constructed a prognostic signature based on four GT genes using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses in The Cancer Genome Atlas (TCGA) dataset. Next, the risk score of each patient was calculated, and HCC patients were divided into high- and low-risk groups. Kaplan–Meier analysis showed that the survival rate of high-risk patients was significantly lower than that of low-risk patients. Receiver operating characteristic (ROC) curves assessed that risk scores calculated with a four-gene signature could predict 3- and 5-year overall survival (OS) of HCC patients, revealing the prognostic ability of this gene signature. Moreover, univariate and multivariate Cox regression analyses demonstrated that the risk score was an independent prognostic factor of HCC. Finally, functional analysis revealed that immune-related pathways were enriched and the immune status was different between the two risk groups in HCC. In summary, the novel GT gene signature could be used for prognostic prediction of HCC. Thus, targeting the GT genes may serve as an alternative treatment strategy for HCC.
Fuzzy Medical Computer Vision Image Restoration and Visual Application
Authors: Tang Yi , Qiu Jin , Gao Ming
Published: June 2022

In order to shorten the image registration time and improve the imaging quality, this paper proposes a fuzzy medical computer vision image information recovery algorithm based on the fuzzy sparse representation algorithm. Firstly, by constructing a computer vision image acquisition model, the visual feature quantity of the fuzzy medical computer vision image is extracted, and the feature registration design of the fuzzy medical computer vision image is carried out by using the 3D visual reconstruction technology. Then, by establishing a multidimensional histogram structure model, the wavelet multidimensional scale feature detection method is used to achieve grayscale feature extraction of fuzzy medical computer vision images. Finally, the fuzzy sparse representation algorithm is used to automatically optimize the fuzzy medical computer vision images. The experimental results show that the proposed method has a short image information registration time, less than 10 ms, and has a high peak PSNR. When the number of pixels is 700, its peak PSNR can reach 83.5 dB, which is suitable for computer image restoration.