bluuebunny/crossref_metadata_2025 huggingface dataset:
Potential of heart fatty-acid binding protein, neurofilament light, interleukin-10 and S100 calcium-binding protein B in the acute diagnostics and severity assessment of traumatic brain injury
Authors: Koivikko Pia , Posti Jussi P , Mohammadian Mehrbod , Lagerstedt Linnea , Azurmendi Leire , Hossain Iftakher , Katila Ari J , Menon David , Newcombe Virginia F J , Hutchinson Peter John , Maanpää Henna-Riikka , Tallus Jussi , Zetterberg Henrik , Blennow Kaj , Tenovuo Olli , Sanchez Jean-Charles , Takala Riikka S K
Published: December 2021

Background

There is substantial interest in blood biomarkers as fast and objective diagnostic tools for traumatic brain injury (TBI) in the acute setting.

Methods

Adult patients (≥18) with TBI of any severity and indications for CT scanning and orthopaedic injury controls were prospectively recruited during 2011–2013 at Turku University Hospital, Finland. The severity of TBI was classified with GCS: GCS 13–15 was classified as mild (mTBI); GCS 9–12 as moderate (moTBI) and GCS 3–8 as severe (sTBI). Serum samples were collected within 24 hours of admission and biomarker levels analysed with high-performance kits. The ability of biomarkers to distinguish between severity of TBI and CT-positive and CT-negative patients was assessed.

Results

Among 189 patients recruited, neurofilament light (NF-L) was obtained from 175 patients with TBI and 40 controls. S100 calcium-binding protein B (S100B), heart fatty-acid binding protein (H-FABP) and interleukin-10 (IL-10) were analysed for 184 patients with TBI and 39 controls. There were statistically significant differences between levels of all biomarkers between the severity classes, but none of the biomarkers distinguished patients with moTBI from patients with sTBI. Patients with mTBI discharged from the ED had lower levels of IL-10 (0.26, IQR=0.21, 0.39 pg/mL), H-FABP (4.15, IQR=2.72, 5.83 ng/mL) and NF-L (8.6, IQR=6.35, 15.98 pg/mL) compared with those admitted to the neurosurgical ward, IL-10 (0.55, IQR=0.31, 1.42 pg/mL), H-FABP (6.022, IQR=4.19, 20.72 ng/mL) and NF-L (13.95, IQR=8.33, 19.93 pg/mL). We observed higher levels of H-FABP and NF-L in older patients with mTBI. None of the biomarkers or their combinations was able to distinguish CT-positive (n=36) or CT-negative (n=58) patients with mTBI from controls.

Conclusions

S100B, H-FABP, NF-L and IL-10 levels in patients with mTBI were significantly lower than in patients with moTBI and sTBI but alone or in combination, were unable to distinguish patients with mTBI from orthopaedic controls. This suggests these biomarkers cannot be used alone to diagnose mTBI in trauma patients in the acute setting.
Redefining WILD syndrome: a primary lymphatic dysplasia with congenital multisegmental lymphoedema, cutaneous lymphovascular malformation, CD4 lymphopaenia and warts
Authors: Mansour Sahar , Josephs Katherine S , Ostergaard Pia , Gordon Kristiana , Van Zanten Malou , Pearce Julian , Jeffery Steve , Keeley Vaughan , Riches Katie , Kreuter Alexander , Wieland Ulrike , Hägerling René , Ratnam Lakshmi , Sackey Ege , Grigoriadis Dionysios , Ho Bernard , Smith Frances , Rauter Elisabeth , Mortimer Peter , Macallan Derek
Published: December 2021

Background

Primary lymphoedema (PL) syndromes are increasingly recognised as presentations of complex genetic disease, with at least 20 identified causative genes. Recognition of clinical patterns is key to diagnosis, research and therapeutics. The defining criteria for one such clinical syndrome, ‘WILD syndrome’ (Warts,Immunodeficiency,Lymphoedema and anogenitalDysplasia), have previously depended on a single case report.

Methods and results

We present 21 patients (including the first described case) with similar clinical and immunological phenotypes. All had PL affecting multiple segments, with systemic involvement (intestinal lymphangiectasia/pleural or pericardial effusions) in 70% (n=14/20). Most (n=20, 95%) had a distinctive cutaneous lymphovascular malformation on the upper anterior chest wall. Some (n=10, 48%) also had hyperpigmented lesions resembling epidermal naevi (but probably lymphatic in origin). Warts were common (n=17, 81%) and often refractory. In contrast to the previous case report, anogenital dysplasia was uncommon—only found in two further cases (total n=3, 14%). Low CD4 counts and CD4:CD8 ratios typified the syndrome (17 of 19, 89%), but monocyte counts were universally normal, unlikeGATA2deficiency.

Conclusion

WILD syndrome is a previously unrecognised, underdiagnosed generalised PL syndrome. Based on this case series, we redefine WILD as ‘Warts,Immunodeficiency, andLymphaticDysplasia’ and suggest specific diagnostic criteria. The essential criterion is congenital multisegmental PL in a ‘mosaic’ distribution. The major diagnostic features are recurrent warts, cutaneous lymphovascular malformations, systemic involvement (lymphatic dysplasia), genital swelling and CD4 lymphopaenia with normal monocyte counts. The absence of family history suggests a sporadic condition, and the random distribution of swelling implicates mosaic postzygotic mutation as the cause.
Heuristics for Finding Sparse Solutions of Linear Inequalities
Authors: Yang Yichen , Liu Zhaohui
Published: December 2021

In this paper, we consider the problem of finding a sparse solution, with a minimal number of nonzero components, for a set of linear inequalities. This optimization problem is combinatorial and arises in various fields such as machine learning and compressed sensing. We present three new heuristics for the problem. The first two are greedy algorithms minimizing the sum of infeasibilities in the primal and dual spaces with different selection rules. The third heuristic is a combination of the greedy heuristic in the dual space and a local search algorithm. In numerical experiments, our proposed heuristics are compared with the weighted-[Formula: see text] algorithm and DCA programming with three different non-convex approximations of the zero norm. The computational results demonstrate the efficiency of our methods.
The quantum dynamics of a mesoscopic driven RLC circuit consisting of a linear inductor, a linear resistor and a nonlinear capacitor
Authors: Zamani A. , Pahlavani H.
Published: December 2021

The nonlinear capacitor that obeys of a cubic polynomial voltage–charge relation (usually a power series in charge) is introduced. The quantum theory for a mesoscopic electric circuit with charge discreteness is investigated, and the Hamiltonian of a quantum mesoscopic electrical circuit comprised by a linear inductor, a linear resistor and a nonlinear capacitor under the influence of a time-dependent external source is expressed. Using the numerical solution approaches, a good analytic approximate solution for the quantum cubic Duffing equation is found. Based on this, the persistent current is obtained antically. The energy spectrum of such nonlinear electrical circuit has been found. The dependency of the persistent current and spectral property equations to linear and nonlinear parameters is discussed by the numerical simulations method, and the quantum dynamical behavior of these parameters is studied.
Image Matting: A Comprehensive Survey on Techniques, Comparative Analysis, Applications and Future Scope
Authors: Lepcha Dawa Chyophel , Goyal Bhawna , Dogra Ayush
Published: December 2021

In the era of rapid growth of technologies, image matting plays a key role in image and video editing along with image composition. In many significant real-world applications such as film production, it has been widely used for visual effects, virtual zoom, image translation, image editing and video editing. With recent advancements in digital cameras, both professionals and consumers have become increasingly involved in matting techniques to facilitate image editing activities. Image matting plays an important role to estimate alpha matte in the unknown region to distinguish foreground from the background region of an image using an input image and the corresponding trimap of an image which represents a foreground and unknown region. Numerous image matting techniques have been proposed recently to extract high-quality matte from image and video sequences. This paper illustrates a systematic overview of the current image and video matting techniques mostly emphasis on the current and advanced algorithms proposed recently. In general, image matting techniques have been categorized according to their underlying approaches, namely, sampling-based, propagation-based, combination of sampling and propagation-based and deep learning-based algorithms. The traditional image matting algorithms depend primarily on color information to predict alpha matte such as sampling-based, propagation-based or combination of sampling and propagation-based algorithms. However, these techniques mostly use low-level features and suffer from high-level background which tends to produce unwanted artifacts when color is same or semi-transparent in the foreground object. Image matting techniques based on deep learning have recently introduced to address the shortcomings of traditional algorithms. Rather than simply depending on the color information, it uses deep learning mechanism to estimate the alpha matte using an input image and the trimap of an image. A comprehensive survey on recent image matting algorithms and in-depth comparative analysis of these algorithms has been thoroughly discussed in this paper.
Reconstructing a quantum state with a variational autoencoder
Authors: Chen Chuangtao , He Zhimin , Huang Zhiming , Situ Haozhen
Published: December 2021

Quantum state tomography (QST) is an important and challenging task in the field of quantum information, which has attracted a lot of attentions in recent years. Machine learning models can provide a classical representation of the quantum state after trained on the measurement outcomes, which are part of effective techniques to solve QST problem. In this work, we use a variational autoencoder (VAE) to learn the measurement distribution of two quantum states generated by MPS circuits. We first consider the Greenberger–Horne–Zeilinger (GHZ) state which can be generated by a simple MPS circuit. Simulation results show that a VAE can reconstruct 3- to 8-qubit GHZ states with a high fidelity, i.e., 0.99, and is robust to depolarizing noise. The minimum number ([Formula: see text]) of training samples required to reconstruct the GHZ state up to 0.99 fidelity scales approximately linearly with the number of qubits ([Formula: see text]). However, for the quantum state generated by a complex MPS circuit, [Formula: see text] increases exponentially with [Formula: see text], especially for the quantum state with high entanglement entropy.
A Spring Structure Triboelectric Nanogenerator for Human Gait Monitoring System
Authors: Cai Jun , Zhang Zhongxing
Published: December 2021

In recent years, many researchers have developed the triboelectric nanogenerators (TENGs) technology to harvest mechanical energy. Here, we proposed a spring-like supporting structure triboelectric nanogenerator (S-TENG) to gain mechanical energy and translate them into electrical energy. From the results, the open-circuit voltage ([Formula: see text]) of S-TENG can arrive at 390[Formula: see text]V, and the short-circuit current ([Formula: see text]) of S-TENG can reach 13.13[Formula: see text][Formula: see text]A. Also, the transferred charge of S-TENG can get to 130[Formula: see text]nC, and as for the maximum output power of S-TENG with the size of [Formula: see text][Formula: see text]cm, it can reach 1.44[Formula: see text]mW. Besides, the electrical output signal of S-TENG can reflect the human motion state such as walking, running and jumping. This design not only greatly promoted the TENGs in mechanical energy harvesting but also the development of self-powered human motion sensor.
Route Optimization via Environment-Aware Deep Network and Reinforcement Learning
Authors: Guo Pengzhan , Xiao Keli , Ye Zeyang , Zhu Wei
Published: December 2021

Vehicle mobility optimization in urban areas is a long-standing problem in smart city and spatial data analysis. Given the complex urban scenario and unpredictable social events, our work focuses on developing a mobile sequential recommendation system to maximize the profitability of vehicle service providers (e.g., taxi drivers). In particular, we treat the dynamic route optimization problem as a long-term sequential decision-making task. A reinforcement-learning framework is proposed to tackle this problem, by integrating a self-check mechanism and a deep neural network for customer pick-up point monitoring. To account for unexpected situations (e.g., the COVID-19 outbreak), our method is designed to be capable of handling related environment changes with a self-adaptive parameter determination mechanism. Based on the yellow taxi data in New York City and vicinity before and after the COVID-19 outbreak, we have conducted comprehensive experiments to evaluate the effectiveness of our method. The results show consistently excellent performance, from hourly to weekly measures, to support the superiority of our method over the state-of-the-art methods (i.e., with more than 98% improvement in terms of the profitability for taxi drivers).
A Framework for Open Civic Design: Integrating Public Participation, Crowdsourcing, and Design Thinking
Authors: Reynante Brandon , Dow Steven P. , Mahyar Narges
Published: December 2021

Civic problems are often too complex to solve through traditional top-down strategies. Various governments and civic initiatives have explored more community-driven strategies where citizens get involved with defining problems and innovating solutions. While certain people may feel more empowered, the public at large often does not have accessible, flexible, and meaningful ways to engage. Prior theoretical frameworks for public participation typically offer a one-size-fits-all model based on face-to-face engagement and fail to recognize the barriers faced by even the most engaged citizens. In this article, we explore a vision for
open civic design
where we integrate theoretical frameworks from public engagement, crowdsourcing, and design thinking to consider the role technology can play in lowering barriers to large-scale participation, scaffolding problem-solving activities, and providing flexible options that cater to individuals’ skills, availability, and interests. We describe our novel theoretical framework and analyze the key goals associated with this vision: (1) to promote inclusive and sustained participation in civics; (2) to facilitate effective management of large-scale participation; and (3) to provide a structured process for achieving effective solutions. We present case studies of existing civic design initiatives and discuss challenges, limitations, and future work related to operationalizing, implementing, and testing this framework.
Firing rate trajectories of human motor units during activity-dependent muscle potentiation
Authors: Zero Alexander M. , Kirk Eric A. , Rice Charles L.
Published: December 2021

During activity-dependent muscle potentiation (ADP), initial motor unit firing rate (MUFR) acceleration and the occurrence of MUFR trajectory saturation as a function of increasing contraction intensity were assessed. With no ADP (control), trajectories were more likely to accelerate and saturate (16/25 units) compared with voluntary- and stimulated-induced ADP conditions (4/25 and 8/25 units, respectively) that were fit better linearly. Therefore, during ADP, an attenuated intrinsic response to voluntary synaptic inputs occurs.
CHOP is dispensable for exercise-induced increases in GDF15
Authors: Townsend Logan K. , Medak Kyle , Weber Alyssa J. , Dibe Hana , Shamshoum Hesham , Wright David C.
Published: December 2021

GDF15 is expressed in a wide range of tissues, is a marker of cellular stress, and has been shown to be regulated by the ER stress protein CHOP. Although exercise increases GDF15, the mechanisms mediating this effect have not been elucidated. Using various models of altered ER stress, we demonstrate that exercise-induced increases in GDF15 occur independent of ER stress/CHOP.
Critical environmental limits for young, healthy adults (PSU HEAT Project)
Authors: Wolf S. Tony , Cottle Rachel M. , Vecellio Daniel J. , Kenney W. Larry
Published: December 2021

Critical environmental limits are those combinations of temperature and humidity above which heat balance cannot be maintained, placing individuals at increased risk of heat-related illness. Those limits have been investigated in young adults during exercise at 30% V̇o2max, but not during metabolic rates that approximate those of light activities of daily living. Herein, we establish critical environmental limits for young adults at two metabolic rates that reflect activities of daily living and leisurely walking.
Evaluating the 35°C wet-bulb temperature adaptability threshold for young, healthy subjects (PSU HEAT Project)
Authors: Vecellio Daniel J. , Wolf S. Tony , Cottle Rachel M. , Kenney W. Larry
Published: December 2021

This study is the first to use empirical physiological observations to examine the well-publicized theoretical 35°C wet-bulb temperature limit for human to extreme environments. We find that uncompensable heat stress in humid environments occurs in young, healthy adults at wet-bulb temperatures significantly lower than 35°C. In addition, uncompensable heat stress occurs at widely different wet-bulb temperatures as a function of ambient vapor pressure.
Rapid Classification and Analysis for E-Commerce Goods Based on Multitask Learning
Authors: Liu Nana
Published: December 2021

Today’s E-commerce is hot, while the categorization of goods cannot be handled better, especially to achieve the demand of multiple tasks. In this paper, we propose a multitask learning model based on a CNN in parallel with a BiLSTM optimized by an attention mechanism as a training network for E-commerce. The results showed that the fast classification task of E-commerce was performed using only 10% of the total number of products. The experimental results show that the accuracy of w-item2vec for product classification can be close to 50% with only 10% of the training data. Both models significantly outperform other models in terms of classification accuracy.
Online Automatic Diagnosis System of Cardiac Arrhythmias Based on MIT-BIH ECG Database
Authors: Yan Wei , Zhang Zhen
Published: December 2021

Arrhythmias are a relatively common type of cardiovascular disease. Most cardiovascular diseases are often accompanied by arrhythmias. In clinical practice, an electrocardiogram (ECG) can be used as a primary diagnostic tool for cardiac activity and is commonly used to detect arrhythmias. Based on the hidden and sudden nature of the MIT-BIH ECG database signal and the small-signal amplitude, this paper constructs a hybrid model for the temporal correlation characteristics of the MIT-BIH ECG database data, to learn the deep-seated essential features of the target data, combine the characteristics of the information processing mechanism of the arrhythmia online automatic diagnosis system, and automatically extract the spatial features and temporal characteristics of the diagnostic data. First, a combination of median filter and bandstop filter is used to preprocess the data in the ECG database with individual differences in ECG waveforms, and there are problems of feature inaccuracy and useful feature omission which cannot effectively extract the features implied behind the massive ECG signals. Its diagnostic algorithm integrates feature extraction and classification into one, which avoids some bias in the feature extraction process and provides a new idea for the automatic diagnosis of cardiovascular diseases. To address the problem of feature importance variability in the temporal data of the MIT-BIH ECG database, a hybrid model is constructed by introducing algorithms in deep neural networks, which can enhance its diagnostic efficiency.
The Effect of Superoxide Dismutase on Inhibition of Acute Kidney Injury Induced by Sepsis Based on Kidney Tissue Histology and Murine Sepsis Score
Authors: Ismy Jufitriani , Syukri Maimun , Emril Dessy R. , Sekarwana Nanan , Ismy Jufriady , Suhanda Rachmad
Published: December 2021

Sepsis is one of the leading causes contributing to the incidence of acute kidney injury (AKI). Oxidative stress can be used as the main approach against sepsis-induced AKI. One of the primary antioxidants that plays a role in warding off oxidative stress is superoxide dismutase (SOD). This research aimed to observe the effect of antioxidant SOD in inhibiting sepsis in AKI based on kidney tissue histopathology. The research method was an experimental laboratory with a post-test-only control group design. Twenty-five adult male rats aged 12–16 weeks, weighing between 200 and 250 g, were randomly divided into five groups: Group I, as a positive control, where rats were injected with lipopolysaccharides (LPS); Group II, as a negative control; Group III, as treatment 1, where rats were injected with LPS and administered orally with SOD (Glisodin®) 250 IU daily; Group IV, as treatment 2, where rats were injected with LPS and administered orally with SOD (Glisodin®) 500 IU daily; and Group V, as treatment 2, where rats were injected with LPS and administered orally with SOD (Glisodin®) 1000 IU daily. Rats were administered with SOD (Glisodin®) by oral gavage with a flexible feeding tube for 16 weeks, given once daily in the morning, and then injected with LPS of 10 mg/kg body weight. Glisodin SOD had a significant effect on murine sepsis score (MSS). MSS influenced the tubular injury score linearly. We conclude that the optimal dose of SOD at 1000 IU for inhibiting sepsis-induced AKI incidence is compared to SOD at a dose of 250 and 500 IU. The antioxidant effect of SOD can prevent sepsis-induced AKI with oxidative stress events.
Three‐Dimensional Stochastic Seepage Field Analysis of Multimedia Embankment
Authors: Zhao Xiaoming , Shang Shiyu , Yang Yuanlin , Hu Mingming
Published: December 2021

The soil hydraulic conductivity of an embankment has strong spatial variability due to the spatiotemporal variation, both natural and artificial. The strong randomness of the hydraulic conductivity can be expressed by the coefficient of variation (COV) and the fluctuation scale θ. Moreover, different coefficients of variation and fluctuation scales correspond to different random field structures. To study the characteristics of the three‐dimensional stochastic seepage field in an embankment under different COVs and fluctuation scales, we generate a three‐dimensional random field of the hydraulic conductivity of multimedia embankment based on the local average subdivision technique. In particular, a calculation method for a three‐dimensional random seepage field based on the Monte Carlo method combined with a three‐dimensional multimedia random field and a deterministic analysis is proposed. The results showed that after three thousand realizations and considering the randomness of the hydraulic conductivity, the position of the free surface of each section in the embankment differed. The mean value of the total head decreased when the COV increased. Furthermore, when the COV was small, the change in the total head with anisotropy ratio was not evident, while the COV was large. The mean value of the total head increased with the anisotropy ratio. When the anisotropy ratio increased, the mean value of the standard deviation of the total head increased first and then decreased.
Prevalence of Shiga Toxin-Producing Escherichia coli O157 and Non-O157 Serogroups Isolated from Fresh Raw Beef Meat Samples in an Industrial Slaughterhouse
Authors: Babolhavaeji Kiandokht , Shokoohizadeh Leili , Yavari Morteza , Moradi Abbas , Alikhani Mohammad Yousef
Published: December 2021

Background. The aims of the current study are the identification of O157 and non-O157 Shiga Toxin-Producing Escherichia coli (STEC) serogroups isolated from fresh raw beef meat samples in an industrial slaughterhouse, determination of antimicrobial resistance patterns, and genetic linkage of STEC isolates. Materials and Methods. A total of 110 beef samples were collected from the depth of the rump of cattle slaughtered at Hamadan industrial slaughterhouse. After detection of E. coli isolates, STEC strains were identified according to PCR for stx1, stx2, eaeA, and hlyA virulence genes, and STEC serogroups (O157 and non-O157) were identified by PCR. The genetic linkage of STEC isolates was analyzed by the ERIC- (Enterobacterial Repetitive Intergenic Consensus-) PCR method. The antimicrobial susceptibility of STEC isolates was detected by the disk diffusion method according to CLSI guidelines. Results. Among 110 collected beef samples, 77 (70%) were positive for E. coli. The prevalence of STEC in E. coli isolates was 8 (10.4%). The overall prevalence of O157 and non-O157 STEC isolates was 12.5% (one isolate) and 87.5% (7 isolates), respectively. The hemolysin gene was detected in 25% (2 isolates) of STEC strains. Evaluation of antibiotic resistance indicated that 100% of STEC isolates were resistant to ampicillin, ampicillin-sulbactam, amoxicillin-clavulanic acid, and cefazolin. Resistance to tetracycline and ciprofloxacin was detected in 62.5% and 12.5% of isolates, respectively. The analysis of the ERIC-PCR results showed five different ERIC types among the STEC isolates. Conclusion. The isolation of different clones STECs from beef and the presence of antibiotic-resistant isolates indicate that more attention should be paid to the hygiene of slaughterhouses.
Defending against Internal Attacks in Healthcare-Based WSNs
Authors: Wei Zhe , Yu Shuyan , Ma Wancheng
Published: December 2021

In view of the spatiotemporal limitations of traditional healthcare services, the use of wireless communication has become one of the main development directions for the medical system. Compared with the traditional methods, applying the potential and benefits of the wireless sensor networks has more advantages such as low cost, simplicity, and flexible data acquisition. However, due to the limited resources of the individual wireless sensor nodes, traditional security solutions for defending against internal attacks cannot be directly used in healthcare based wireless sensor networks. To address this issue, a negative binomial distribution trust with energy consideration is proposed in this study. The proposed method is lightweight and suitable to be operated on the individual healthcare sensors. Simulations show that it can effectively deal with the internal attacks while taking the energy saving into consideration.
Comparing Hysteretic Energy and Ductility Uniform Annual Failure Rate Spectra for Traditional and a Spectral Shape‐Based Intensity Measure
Authors: Carvajal Joel , Bojórquez Edén , Ruiz Sonia , Bojórquez Juan , Reyes-Salazar Alfredo , Rodríguez Ali , Niño Mauro , Ruiz-García Jorge , López-Almansa Francisco , Torres José
Published: December 2021

In this study, with the objective to develop a reliability‐based seismic design tool, ductility and dissipated hysteretic energy uniform annual failure rate (UAFR) spectra are obtained and compared using the spectral acceleration at first mode of vibration of the structure Sa(T1) and the well‐known spectral shape‐based intensity measure INp. Notice that this is the first time in the literature that UAFR spectra are obtained for the advanced spectral shape intensity measure INp. For this aim, 110 simulated ground motions recorded from the soft soil of Mexico City were selected due to their large energy amount demanded to the structures; moreover, four elastoplastic hysteretic behavior models are considered for the dynamic analyses with post‐yielding stiffness of 0, 3, 5, and 10%. It is observed that the use of elasto‐perfectly plastic models provided similar UAFR spectra in comparison with hysteretic models with different post‐yielding stiffness. This conclusion is valid for the two selected intensity measures. In addition, the lateral resistance required to achieve similar structural reliability levels is larger when the INp intensity measure is used, especially for buildings with vibration periods equal or larger than the soil period, in such a way that the traditional use of Sa(T1) could provide structures with less structural reliability levels.
Second-Generation Tyrosine Kinase Inhibitor Discontinuation in Chronic Myeloid Leukemia Patients with Stable Deep Molecular Response: A Systematic Review and a Meta-Analysis
Authors: Di Qiongnan , Deng Huiyang , Zhao Yingxin , Li Bo-ya , Qin Ling
Published: December 2021

The treatment with 2nd-generation tyrosine kinase inhibitors (2G-TKIs), namely, dasatinib and nilotinib, has been reported to have faster and deeper responses in newly diagnosed chronic phase-chronic myeloid leukemia (CP-CML) patients as compared with imatinab. A number of studies on the discontinuation of 2G-TKIs have been conducted and recently published. A meta-analysis was conducted in this study to assess the rate of treatment-free remission (TFR) rate as well as the long-term safety of 2G-TKI discontinuation in CML patients with stable deep molecular response (DMR). 517 patients were recruited in 5 single-armed, prospective cohort studies. The overall weighted mean TFR rate at the follow-up of 12 months reached 57% (95% CI 51-64%;

I

2

=
56.4

%). The weighted mean TFR rate at the 24-month follow-up was 53% (95% CI 47-60%;

I

2

=
47.1

%). The loss of TFR was primarily concentrated in the first 12 months. 96.5% of patients, having restarted TKI therapy after a molecular relapse, achieved major molecular response (MMR) rapidly. There were four deaths at the two-year follow-up. As suggested from the results of the final study, 2G-TKI discontinuation in CML patients with stable DMR was reported to be feasible. Relapsed patients were retreated with 2G-TKI, and over 95% of patients could reach MMR. Almost no deaths occurred due to adverse events in two years after discontinuation, and more than half of the patients could maintain a TFR.
Joint Deep-Learning-Enabled Impact of Holistic Care on Line Coagulation in Hemodialysis
Authors: Zhang Haisu , Huang Wei
Published: December 2021

In order to investigate the impact of holistic care on line coagulation and safety in hemodialysis and to address limitations of the conventional ultrasound flow vector imaging (VFM) technique, which requires proprietary software to acquire raw Doppler and scatter tracking data, a combined deep-learning-enabled holistic care approach to line coagulation in hemodialysis is proposed. First, velocity along the direction of the sound beam, which is provided by the color Doppler echocardiogram, is obtained as the radial velocity component using a velocity scale. Moreover, the left ventricular wall contour is automatically identified using a U-Net network and the left ventricular wall velocity is calculated as the boundary condition of continuity equation by a retrained PWC-Net model. Likewise, the velocity component of each blood mass in the vertical direction of the sound beam is obtained by solving the continuity equation (i.e. tangential velocity component). Finally, the velocity vector map of cardiac flow field was synthesized and visualized in the flow diagram. For this purpose, sixty patients admitted to receive hemodialysis from February 2019 to June 2020 were randomly divided into two groups of 30 patients where the control group implemented conventional care and the study group implemented all-round care on the basis of conventional care. The nursing effects of both groups were compared. Incidence of pipeline coagulation and complications in the study group were lower than those in the control group and the difference was statistically significant (

P
<
0.05

). The nursing detail score, nursing attitude score, nursing professionalism score, and total satisfaction score in the study group were higher than those in the control group and the difference was statistically significant (

P
<
0.05

). Applying all-round nursing in hemodialysis can effectively reduce the incidence of line coagulation complications and improve the safety of hemodialysis, as well as improve patients’ satisfaction with nursing care.
Monitoring of Neuroendocrine Changes in Acute Stage of Severe Craniocerebral Injury by Transcranial Doppler Ultrasound Image Features Based on Artificial Intelligence Algorithm
Authors: Wang Tao , Chen Yizhu , Du Hangxiang , Liu Yongan , Zhang Lidi , Meng Mei
Published: December 2021

This study was aimed at exploring the application value of transcranial Doppler (TCD) based on artificial intelligence algorithm in monitoring the neuroendocrine changes in patients with severe head injury in the acute phase; 80 patients with severe brain injury were included in this study as the study subjects, and they were randomly divided into the control group (conventional TCD) and the experimental group (algorithm-optimized TCD), 40 patients in each group. An artificial intelligence neighborhood segmentation algorithm for TCD images was designed to comprehensively evaluate the application value of this algorithm by measuring the TCD image area segmentation error and running time of this algorithm. In addition, the Glasgow coma scale (GCS) and each neuroendocrine hormone level were used to assess the neuroendocrine status of the patients. The results showed that the running time of the artificial intelligence neighborhood segmentation algorithm for TCD was

3.14
±
1.02
 
s

, which was significantly shorter than

32.23
±
9.56
 
s

of traditional convolutional neural network (CNN) algorithms (

P
<
0.05

). The false rejection rate (FRR) of TCD image area segmentation of this algorithm was significantly reduced, and the false acceptance rate (FAR) and true acceptance rate (TAR) were significantly increased (

P
<
0.05

). The consistent rate of the GCS score and Doppler ultrasound imaging diagnosis results in the experimental group was 93.8%, which was significantly higher than the 80.3% in the control group (

P
<
0.05

). The consistency rate of Doppler ultrasound imaging diagnosis results of patients in the experimental group with abnormal levels of follicle stimulating hormone (FSH), prolactin (PRL), growth hormone (GH), adrenocorticotropic hormone (ACTH), and thyroid stimulating hormone (TSH) was significantly higher than that of the control group (

P
<
0.05

). In summary, the artificial intelligence neighborhood segmentation algorithm can significantly shorten the processing time of the TCD image and reduce the segmentation error of the image area, which significantly improves the monitoring level of TCD for patients with severe craniocerebral injury and has good clinical application value.
Timing of Acupuncture Treatment in Peripheral Facial Paralysis: A Systematic Review and Meta-Analysis
Authors: Yu Zelin , Shen Mengxia , Shang Wenfang , Wu Jiangxia , Xuan Lihua
Published: December 2021

Objective. Investigate the optimum time of acupuncture treatment in peripheral facial paralysis in order to provide evidence for clinical treatment. Methods. CNKI, Wanfang, PubMed, Cochrane Library, and EMBASE databases were systematically searched from the inception dates to February 20, 2020. Studies limited to participants with acute peripheral facial paralysis treated with acupuncture and patients without information of the stage were excluded. The primary outcomes were effective rate and cure rate (based on facial nerve function scores). This meta-analysis is registered with PROSPERO, number CRD42020169870. Results. 15 randomized controlled trials that enrolled 2847 participants met the selection criteria. There was no significant differences in the effective rate (RR, 1.22; 95% CI, 0.70-2.11) when comparing acupuncture to prednisone therapy in acute facial paralysis. Acupuncture treatment in the acute stage increased both the effective rate (RR, 1.03; 95% CI, 1.00-1.07) and the cure rate (RR, 1.34; 95% CI, 1.14-1.58) compared to that in the nonacute stage. Conclusions. In this meta-analysis, acupuncture showed a better effect in the acute stage than the nonacute stage for participants with peripheral facial paralysis. There was no statistical difference in the effective rate no matter the choice of acupuncture or prednisone therapies in the acute stage. These findings encourage early acupuncture treatment in peripheral facial paralysis.
[Retracted] Green Machining Characteristics Study of Al‐6063 in CNC Milling Using Taguchi Method and Grey Relational Analysis
Authors: Suresh Kumar R. , Senthil Kumar S. , Murugan K. , Hailegiorgis Sintayehu Mekuria
Published: December 2021

Green machining strategies in the manufacturing sector help to maintain the product value by considering the environmental impacts. Also, improvisation in the quality contribution of the parts can minimize the environmental consequences by improving resource efficiency, specifically in terms of coolants used in machining. Certain hazardous impacts have been witnessed because of longer exposure to such a machining environment. To address it, many researchers have concentrated on providing a healthy machining environment either by introducing dry machining or by minimum quantity lubrication (MQL). The proposed study addresses this context. The influence of these tactics on the attained surface quality of Al‐6063 is quantified in this paper in terms of surface integrity (Ra) and removal rate of material (MRR). The study involves single‐response optimization using the Taguchi design and multiresponse optimization using grey relational analysis (GRA). The results reveal that the depth of cut (Dc) and spindle speed (Ss) have the greatest impact on Ra and MRR. The machinability of Al‐6063 is examined by considering the key machinability parameters, such as the spindle speed (Ss), feed rate (Fr), and the depth of cut (Dc), to arrive at the best possible surface roughness and removal rate of the material. As a typical Taguchi approach cannot perform multiresponse optimization, grey relational analysis is used. The grey relational analysis combined with Taguchi gives a novel methodology for multioptimization. The entire study is performed in dry condition and under minimum quantity lubrication. The results suggest that the responses are highly influenced by the depth of cut and spindle speed.
Serosurvey and Molecular Detection of Toxoplasma gondii in Dogs in Rural Areas of Kazeroun District, Fars Province, Southern Iran
Authors: Rezaei Zahra , Zeighami Ali , Shahriarirad Reza , Erfani Amirhossein , Rastegarian Mohammad , Arefkhah Nasir , Pourabbas Bahman , Ghorbani Fariba , Sarkari Bahador
Published: December 2021

Background. Toxoplasma gondii is an intracellular protozoan parasite responsible for systemic disease in a wide range of warm-blooded animals. The current study is aimed at evaluating the prevalence of Toxoplasma infection in dogs, using serological and molecular methods in rural areas in Kazeroun Township, Fars province, southern Iran. Methods. Blood samples were obtained from 60 clinically healthy dogs with an age range of 1 to 7 years in three rural areas of Fars province, southern Iran. Sera and buffy coats were used to assess the T. gondii infection using both modified agglutination test (MAT) and real-time PCR. Results. Antibodies against T. gondii were detected in 5 out of 60 (8.3%) dogs by the MAT method, and T. gondii DNA was detected in 17 out of 60 (28.3%) studied animals. There was no significant association between sex and seropositivity to Toxoplasma (

p
>
0.05

). Fair agreement (

kappa
=
0.27

) was seen between molecular and serological findings where three dogs with positive serological results had a positive molecular test. Conclusion. Findings of the present study show a relatively high prevalence of T. gondii infection in dogs in rural areas in Fars province, southern Iran. Finding the parasite genotype in dogs deserves further study.
The Impact of Innovative Industrial Cluster Policy on Regional Innovation: Evidence from a Quasi-Natural Experiment in China
Authors: Wang Huan , Guo Jinhua
Published: December 2021

As important carriers of local innovation activities, innovative industrial clusters are attracting increasing attention. Therefore, several countries have started promotion policies for innovative industrial clusters. However, there are few empirical studies on relevant policies. This paper investigates the impact of China’s “innovative industrial cluster pilot” (IICP) policy on regional innovation. Taking the implementation of IICP policy as a quasi-natural experiment and using the panel data of 266 prefecture-level cities in China in 2008-2019, this paper provides strong evidence that IICP policy promotes regional innovation. The conclusion still holds after a battery of robustness checks. The heterogeneity test shows that the promoting effect of IICP policy on innovation is more significant in central and western region than in eastern region. Moreover, the lower the city administrative level and the lower the dependence on natural resource, the more prominent the innovation effect of IICP policy. Further, the mechanism test shows that the IICP policy can promote regional innovation indirectly by strengthening government support for innovation and attracting the agglomeration of science and technological talents, but the mediation effect of industrial structure has not been verified.
On Fixed Point Findings for Diverse Contractions in
b
Dislocated-Multiplicative Metric Spaces
Authors: Kamal A. , Abd-Elal Asmaa M.
Published: December 2021

In our present research study, we present the idea of

b

dislocated-multiplicative metric space (abbrev.

b
d

-multiplicative metric space) that is generalization of

b

-multiplicative metric space and dislocated-multiplicative metric space. Furthermore, we prove some of the fixed point theorems in

b
d

-multiplicative metric spaces. Also, we get common fixed point findings for fuzzy mappings in these spaces. Our findings are improved and more generalized form of several findings (see, e.g., [5, 6]).
TCM Regulates PI3K/Akt Signal Pathway to Intervene Atherosclerotic Cardiovascular Disease
Authors: Liu Jiali , Xu Pangao , Liu Dekun , Wang Ruiqing , Cui Shengnan , Zhang Qiuyan , Li Yunlun , Yang Wenqing , Zhang Dan
Published: December 2021

Vascular endothelial injury is the initial stage of atherosclerosis (AS). Stimulating and activating the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway can regulate the expression of vascular endothelial cytokines, thus affecting the occurrence and development of AS. In addition, the PI3K/Akt signaling pathway can regulate the polarization and survival of macrophages and the expression of inflammatory factors and platelet function, thus influencing the progression of AS. In recent years, traditional Chinese medicine (TCM) has been widely recognized for its advantages of fewer side effects, multiple pathways, and multiple targets. Also, the research of TCM regulation of AS via the PI3K/Akt signaling pathway has achieved certain results. This study aimed to analyze the characteristics of the PI3K/Akt signaling pathway and its role in the pathogenesis of AS, as well as the role of Chinese medicine in regulating the PI3K/Akt signaling pathway. The findings are expected to provide a theoretical basis for the clinical treatment and pathological mechanism research of AS.
Interaction of Self-Sustained Pulses in Tunnel-Diode Oscillator Lattices
Authors: Narahara Koichi
Published: December 2021

A one-dimensional lattice in tunnel-diode (TD) oscillators supports self-sustained solitary pulses resulting from the balance between gain and attenuation. By applying the reduction theory to the device’s model equation, it is found that two relatively distant pulses moving in the lattice are mutually affected by a repulsive interaction. This property can be efficiently utilized in equalizing pulse positions to achieve jitter elimination. In particular, when two pulses rotate in a small, closed lattice, they separate evenly at the asymptotic limit. As a result, the lattice loop can provide an efficient platform to obtain low-phase-noise multiphase oscillatory signals. In this work, the interaction between two self-sustained pulses in a TD-oscillator lattice is examined, and the properties of interpulse interaction are validated by conducting several measurements using a test breadboarded lattice.
Approximate and Exact Solutions to Fractional Order Cauchy Reaction-Diffusion Equations by New Combine Techniques
Authors: Khan Adnan , Liaqat Muhammad Imran , Younis Muhammad , Alam Ashraful
Published: December 2021

In this paper, we present a simple and efficient novel semianalytic method to acquire approximate and exact solutions for the fractional order Cauchy reaction-diffusion equations (CRDEs). The fractional order derivative operator is measured in the Caputo sense. This novel method is based on the combinations of Elzaki transform method (ETM) and residual power series method (RPSM). The proposed method is called Elzaki residual power series method (ERPSM). The proposed method is based on the new form of fractional Taylor’s series, which constructs solution in the form of a convergent series. As in the RPSM, during establishing the coefficients for a series, it is required to compute the fractional derivatives every time. While ERPSM only requires the concept of the limit at zero in establishing the coefficients for the series, consequently scarce calculations give us the coefficients. The recommended method resolves nonlinear problems deprived of utilizing Adomian polynomials or He’s polynomials which is the advantage of this method over Adomain decomposition method (ADM) and homotopy-perturbation method (HTM). To study the effectiveness and reliability of ERPSM for partial differential equations (PDEs), absolute errors of three problems are inspected. In addition, numerical and graphical consequences are also recognized at diverse values of fractional order derivatives. Outcomes demonstrate that our novel method is simple, precise, applicable, and effectual.
Research on the Optimization Method of Visual Effect of Outdoor Interactive Advertising Assisted by New Media Technology and Big Data Analysis
Authors: Gan Zhinan , Tsai Sang-Bing
Published: December 2021

Along with the development and promotion of Internet technology, new media are increasingly diversified, enriching and changing our lives. This paper focuses on outdoor interactive advertising as a communication method, analyzing its creative features and applications. Unlike traditional advertising, where audiences receive passively, new media interactive advertising establishes a more direct communication method for consumers and products, creating different sensory stimulation and emotional experience environments according to the characteristics of products and conducting a series of interactions with consumers’ sensory systems such as vision, hearing, smell, taste, and touch. The advertising method has also changed from passive reception to active participation. Finally, combining the characteristics of accurate delivery and the diversity of presentation forms of interactive advertising under the big data platform, the theme conception and form design of interactive advertising is proposed. The interactive design principles of highlighting the simplicity of the theme are explored. The interactive design principle of highlighting the simplicity of the theme is proposed, and the combination of color, text, and graphics is explored by the aesthetic visual design of the audience and the premise of focusing on the audience’s feelings. Starting from the visual effect of outdoor interactive advertising, the change in the way advertising is conveyed is interpreting to us the arrival of a new communication concept, the arrival of the Internet-centered and technology-centered data integration era. The research in this paper aims to provide useful support for the diversified development of outdoor interactive advertising in the new media environment by exploring how to skillfully realize the creative expression of outdoor interactive advertising in the new media environment.