Search

Workflow scheduling in cloud environments has become a significant topic in both commercial and industrial applications. However, it is still an extraordinarily challenge to generate effective and economical scheduling schemes under the deadline constraint especially for the large scale workflow applications. To address the issue, this paper investigates the cloud workflow scheduling problem with the aim of minimizing the whole cost of workflow execution whereas maintaining its execution time under a predetermined deadline. A novel knowledge-based adaptive discrete water wave optimization (KADWWO) algorithm is developed based on the problem-specific knowledge of cloud workflow scheduling. In the proposed KADWWO, a discrete propagation operator is designed based on the idle time knowledge of hourly-based cost model to adaptively explore the huge search space. The adaptive refraction operator is employed to avoid stagnation and expand the available resource pool. Meanwhile, the dynamic grouping based breaking operator is designed to exploit the excellent block structure knowledge of task allocation scheme and corresponding resource to intensify the local region and accelerate convergence. Extensive simulation experiments on the well-known scientific workflow demonstrate that the KADWWO approach outperforms several recent state-of-the-art algorithms.

This article studies a distributed heterogeneous hybrid flow shop scheduling problem under nonidentical time-of-use electricity tariffs (DHHFSP-NTOU). The makespan and the total electricity charge are considered as the optimization objectives from the view of production and management. The DHHFSP-NTOU considers different processing capabilitie and time-of-use electricity tariffs for each factory. The mixed-integer linear programming (MILP) model of DHHFSP-NTOU is established. To solve the DHHFSP-NTOU, this article proposes an ant colony optimization behavior-based multiobjective evolutionary algorithm based on decomposition (ACO_MOEA/D). A problem-specific ant colony behavior is presented to construct offspring individuals. Eight neighborhoods within the factory and between factories are adopted to improve the quality of the individuals in the archive set. A right-shift movement is used to reduce the electricity charge. A large number of numerical experiments and comprehensive investigations are carried out to test the efficiency and effectiveness of ACO_MOEA/D. The experimental results show that each component (e.g., ant colony behavior, neighborhoods move operators, right-shift movement) contributes to the performance of ACO_MOEA/D. The comparisons with several related algorithms show the superiority of ACO_MOEA/D for solving the DHHFSP-NTOU.

Industrial Internet of Things (IIoT) and Industry 4.0 empower interrelation among manufacturing processes, industrial machines, and utility services. The time-critical data collected from heterogeneous sensing devices are usually communicated to processing points for analysis and aggregation as the basis of IIoT. The IIoTs’ service quality typically depends on data integrity and accuracy, which could be exploited by injecting malicious events such as false data injection and data poisoning attacks. Thus, effective anomaly recognition and explanation are critical for ensuring quality services and empowering security administrators to interpret the causal reasoning of prediction decisions and underlying data evidence. This study proposes an autoencoder-based detection framework using convolutional and recurrent networks to discover cyber threats in IIoT networks and explain the model. A two-step Sliding Window (SW) is applied to learn the latent representations of data features better. Malicious points from the raw time series are transformed into fixed-length series through the first-step SW. Every series is converted into continuous time-reliant subseries via another smaller SW to learn latent representations of malicious events. Fully connected networks use the extracted temporal and spatial features for the classification and explanation of attack events. The empirical results revealed that this framework effectively extracts features that include contexts of malicious patterns. This demonstrated that the proposed framework is robust in detecting malicious events using multiple evaluation metrics and outperforming the contemporary state-of-the-art methods, indicating its suitability as an operative application method in real-world IIoT-based networks.

In robot torts, robots carry out activities that are partially controlled by a human operator. Several legal and economic scholars across the world have argued for the need to rethink legal remedies as we apply them to robot torts. Yet, to date, there exists no general formulation of liability in case of robot accidents, and the proposed solutions differ across jurisdictions. We proceed in our research with a set of two companion papers. In this paper, we present the novel problems posed by robot accidents, and assess the legal challenges and institutional prospects that policymakers face in the regulation of robot torts. In the companion paper, we build on the present analysis and use an economic model to propose a new liability regime which blends negligence-based rules and strict manufacturer liability rules to create optimal incentives for robot torts.

The deep learning based methods have improved the visual tracking precision significantly. However, the background distraction and the high precise localization remain challenging problems. Despite that some methods have fused the deep and shallow layer features to solve these problems, the existing fusion methods, like simply concatenating or adding the features from the different layers, cannot take the advantage of both the deep and shallow layer features fully. In this paper, we propose a new adaptive feature fusion method, called the instance-based feature pyramid (IBFP) to obtain the discriminative high-resolution feature, which not only inherits the discriminative information from the deep layer feature, but also keeps the high precision localization information of the shallow layer feature. For utilizing the deep and shallow features effectively, we design an instance-based upsampling (IBU) module to fuse them, and a compressed space channel selection (CSCS) module to re-weight the feature channels adaptively. We insert the IBU and CSCS modules in the Siamese tracker for end-to-end training and testing. By using the proposed IBU and CSCS modules, we fuse the deep and shallow features in a series manner. Experiments on large-scale benchmark datasets demonstrate that the proposed modules boost the capabilities of distinguishing the targets and the similar distractors and perform favorably against the state-of-the-art.

Background: High methionine-diet (HMD) causes Alzheimer's disease (AD)-like symptoms. Previous studies have shown that Dendrobium nobile Lindle. alkaloids (DNLA) had potential benefits for AD. Object: Whether DNLA can improve AD-like symptoms induced by HMD is to be explored. Method: Mice were fed with 2% HMD diet for 11 weeks, the DNLA20 control group (20 mg/kg), DNLA10 group (10 mg/kg), and DNLA20 group (20 mg/kg) were administrated with DNLA for 3 months. Morris water maze test was used to detect learning and memory ability. Neuron damage was evaluated by HE and Nissl stainings. Levels of homocysteine (Hcy), beta-amyloid 1-42 (Aβ1-42), S-adenosine methionine (SAM), and S-adenosine homocysteine (SAH) were detected by ELISA. Immunofluorescence and western blotting (WB) were used to determine the expression of proteins. CPG island methylation. Results: Morris water maze test revealed that DNLA improved learning and memory dysfunction. HE, Nissl, and immunofluorescence stainings showed that DNLA alleviated neuron damage and reduced the 5-methylcytosine (5-mC), Aβ1-40, and Aβ1-42 levels. DNLA also decreased the levels of Hcy and Aβ1-42 in the serum, along with decreased SAM/SAH levels in the liver tissue. WB results showed that DNLA down-regulated the expression of the amyloid-precursor protein (APP), presenilin-1 (PS1), beta-secretase-1 (BACE1), DNA methyltransferase1 (DNMT1), Aβ1-40, and Aβ1-42 proteins. DNLA also up-regulated the expression of the protein of insulin-degrading enzyme (IDE), neprilysin (NEP), DNMT3a, and DNMT3b. Meanwhile, DNLA increased CPG island methylation levels of APP and BACE1 genes. Conclusions: DNLA alleviated AD-like symptoms induced by HMD via the DNA methylation pathway.

Due to the long latency of accessing services from cloud datacenters, mobile edge computing (MEC) has been proposed to provide the capability of cloud computing in close proximity to mobile users. Mobile devices can offload computation-intensive applications to MEC servers to achieve better performance and reduce power consumption. Owing to user mobility, workloads of MEC servers would vary severely to cause imbalanced loads and incur hotspot servers. Previous studies of power saving and hotspot management apply mechanisms for cloud datacenters to MEC servers, but these studies may not be suitable for MEC servers due to the limited computation and communication capacity. We are motivated to propose a scheme, complementary offloading for hotspot mitigation (COHM), for MEC. COHM consists of mechanisms for MEC servers with different states, namely busy, idle, and available. These mechanisms jointly consider the computation tasks for MEC servers with different states to mitigate hotspots. The simulation results show that COHM can decrease the number of hotspot servers without degrading the quality of service for applications.

The timing of oral refeeding can affect length of stay (LOS) and recovery of acute pancreatitis (AP). However, the optimal timing for oral refeeding is still controversial for AP. This meta-analysis investigated the effects of immediate or early versus delayed oral feeding on mild and moderate AP, regardless of improvement in clinical signs or laboratory indicators.This systematic review and meta-analysis of randomized controlled trials (RCTs) based on data from Embase, Cochrane Library, PubMed, Web of science, and CBM before August 2021. Two researchers independently used Stata16 to extract and analyse study data. Random effect model was performed for meta-analysis to calculate the risk ratio (RR) and standardized mean difference (SMD).8 RCTs were selected, including 748 patients with mild to moderate AP. Patients in IOR (Immediate or early Oral Refeeding) group had less costs [SMD -0.83, 95%CI (-1.17, -0.5), P 0.001] and shorter LOS [SMD -1.01, 95%CI (-1.17, -0.85), P 0.001] than the DOR (Delayed Oral Refeeding) group patients. However, there was no difference in mortality [RR 0.54, 95%CI (0.11, 2.62), P = 0.44], pain relapse rate [RR 0.58, 95%CI (0.25, 1.35), P = 0.27], feeding intolerance rate [RR 0.61, 95%CI (0.28, 1.3), P = 0.2], AP progression rate [RR 0.21, 95%CI (0.04, 1.07), P = 0.06] and overall complications rate [RR 0.41, 95%CI (0.17, 1.01), P = 0.05] between the IOR and DOR groups.Limited data suggest that IOR could reduce LOS and costs without increasing adverse events in mild to moderate AP.

A modular electric vehicle platform enables ability to integrate different control systems in a flexible way. In this paper, a decentralized cooperative control framework is proposed to achieve the integration of active front steering system (AFS) and active suspension system (ASS) by applying a multi-constrained distributed model predictive control (MDMPC) approach, which aims to improve the vehicle lateral stability, ride comfort and roll safety during path tracking. First, a partly decoupled 6-degree-of-freedom half-vehicle dynamics model is constructed. Then, a multi-agent-system (MAS)-based framework is introduced to coordinate AFS and ASS, which allows for the multi-constraints within the information exchange between agents. Through minimizing linear convex combination of objective functions, the cooperative control strategy is ultimately solved by the Pareto-optimality theory. Moreover, vehicle lateral and roll motion stability region described by the phase plane is employed to bound the controllable limits and achieve the dynamic cooperation between AFS and ASS. The simulation and hardware-in-the-loop (HIL) test results show that the proposed framework is effective for coordinating AFS and ASS, thereby enhancing the vehicle lateral and vertical stability during path tracking.

BACKGROUND Right ventricular outflow tract (RVOT) obstruction relief is one of the major procedures during the total correction of tetralogy of Fallot (TOF). Pulmonary insufficiency (PI) is usually inevitable after a transannular incision with a patch repair is performed. Therefore, some surgeons advocate to place a monocusp valve within the transannular patch (TAP) in order to decrease the severity of the PI. However, the monocusp valve seemed not be very effective in some patients who underwent the complete TOF repair. METHODS Patients who had the classic form of TOF between January 2009 and January 2017 and underwent the corrective surgery with a TAP by the same cardiovascular surgeon were identified for further analysis. Clinical information including demographics at operation, perioperative data, and postoperative outcome were collected retrospectively and compared between the group with and without a monocusp valve. RESULTS A total of 24 TOF cases were included in the final analysis, and 16 (66.7%) patients received a monocusp valve placement. The patients' characteristics before and during the surgery were similar between the two groups. The median duration of chest tube drainage after the total correction in the monocusp group was longer than those without the valve (p = 0.04). There was no difference in the immediate postoperative data, including the inflammation/infection status, the duration of mechanical ventilation, and the length of ICU and hospital stay. CONCLUSION Implantation of a monocusp valve during the total TOF correction using a TAP did not bring benefit to improve the immediate postoperative outcomes, especially the duration of the pleural drainage. Further study with a prospective design and a larger number of cases is needed.

BackgroundThe Receptor Binding Domain (RBD) of the SARS-CoV-2 spike protein is the target for many COVID-19 vaccines. Here we report results for phase 1 clinical trial of two COVID-19 vaccine candidates based on recombinant dimeric RBD (d-RBD).MethodsWe performed a randomized, double-blind, phase I clinical trial in the National Centre of Toxicology in Havana. Sixty Cuban volunteers aged 19-59 years were randomized into three groups (20 subjects each): 1) FINLAY-FR-1 (50 mcg d-RBD plus outer membrane vesicles from N. meningitidis); 2) FINLAY-FR-1A-50 mcg d-RBD (three doses); 3) FINLAY-FR-1A-25 mcg d-RDB (three doses). The FINLAY-FR-1 group was randomly divided to receive a third dose of the same vaccine candidate (homologous schedule) or of FINLAY-FR-1A-50 (heterologous schedule). The primary outcomes were safety and reactogenicity. The secondary outcome was vaccine immunogenicity. Humoral response at baseline and following each vaccination was evaluated using live-virus neutralization test, anti-RBD IgG ELISA and in-vitro neutralization test of RBD:hACE2 interaction.ResultsMost adverse events were of mild intensity (63.5%), solicited (58.8%), and local (61.8%); 69.4% with causal association with vaccination. Serious adverse events were not found. The FINLAY-FR-1 group reported more adverse events than the other two groups. After the third dose, anti-RBD seroconversion was 100%, 94.4% and 90% for the FINLAY-FR-1, FINLAY-FR-1A-50 and FINLAY-FR-1A-25 respectively. The in-vitro inhibition of RBD:hACE2 interaction increased after the second dose in all formulations. The geometric mean neutralizing titres after the third dose rose significantly in the group vaccinated with FINLAY-FR-1 with respect to the other formulations and the COVID-19 Convalescent Serum Panel. No differences were found between FINLAY-FR-1 homologous or heterologous schedules.ConclusionsVaccine candidates were safe and immunogenic, and induced live-virus neutralizing antibodies against SARS-CoV-2. The highest values were obtained when outer membrane vesicles were used as adjuvant.Trial registryhttps://rpcec.sld.cu/en/trials/RPCEC00000338-En

Ultrasonography of the breast mass is an important imaging technology for diagnosing breast cancer. In China, ultrasound equipment is widely used in medical institutions. Patients obtain a report with highlighted ultrasonography images through an initial clinical screening. However, analyzing these images manually is highly subjective for the variation in the clinical competence of doctors, resulting in poor consistency and low sensitivity. In this study, an automated breast cancer diagnosis system is developed to increase diagnostic accuracy. The system is deployed on mobile phones, takes a photo of the ultrasound report as input and performs diagnosis on each image. The developed system consists of three subsystems. The first subsystem is to reduce noise in the taken photos, reconstructing high-quality images. We develop the first subsystem based on the frameworks of stacked denoising autoencoders and generative adversarial networks. The second subsystem is to classify images into malignant and non-malignant; to extract high-level features from the images, deep convolutional neural networks are employed. The third subsystem is to detect anomalies in model performances, reducing false negative rates. Generative adversarial networks are utilized to distinguish false negative samples from true negative samples. 18225 breast ultrasonography images and 2416 ultrasound reports are collected to train and evaluate the system. Experimental results show that the performance of our system is comparable to that of human experts. It is believed that this is the first system for breast cancer diagnosis deployed on mobile phones. The developed system is integrated with a cloud computing platform and accessible online to aid in the initial screening and diagnosis of breast cancer, thereby promoting earlier treatment, reducing the morbidity and mortality.

Background: In COVID-19, EGFR production is upregulated in the alveolar epithelial cells. EGFR overexpression further activates STAT-3 and increases lung pathology. The EGFR pathway is also one of the major nodes in pulmonary fibrosis. Methods: Nimotuzumab, a humanized anti-EGFR antibody, was used to treat three patients with severe or moderate COVID-19. The antibody was administered in combination with other drugs included in the national COVID-19 protocol. Results: Nimotuzumab was well tolerated. IL-6 decreased from the first antibody infusion. Clinical symptoms significantly improved after nimotuzumab administration, and the CT scans at discharge showed major resolution of the lung lesions and no signs of fibrosis. Conclusion: Safe anti-EGFR antibodies like nimotuzumab may modulate COVID-19-associated hyperinflammation and prevent fibrosis. Clinical Trial Registration: RPCEC00000369 (RPCEC rpcec.sld.cu)., Lay abstract Background: In COVID-19, the protein EGFR is overactive in the infected lung cells. Methods: Nimotuzumab, an anti-EGFR antibody, was used to treat three patients with severe or moderate COVID-19. The antibody was administered in combination with other drugs included in the national COVID-19 protocol. Results: Nimotuzumab was safe. The most important inflammatory markers decreased from the first administration. The patients’ clinical symptoms and imaging results improved significantly. Conclusion: Anti-EGFR antibodies like nimotuzumab may contribute to the recovery of COVID-19 patients without long-term consequences.

The Internet of Medical Things (IoMT) is increasingly replacing the traditional healthcare systems. However, less focus has been paid to their security against cyber-threats in the implementation of the IoMT and its networks. One of the key reasons can be the challenging task of optimizing typical security solutions to the IoMT networks. And despite the rising admiration of machine learning and deep learning methods in the cyber-security domain (e.g., a threat detection system), most of these methods are acknowledged as a black-box model. The explainable AI (XAI) has become progressively vital to understand the employed learning models to improve trust level and empower security experts to interpret the prediction decisions. The authors propose a highly efficient model named XSRU-IoMT, for effective and timely detection of sophisticated attack vectors in IoMT networks. The proposed model is developed using novel bidirectional simple recurrent units (SRU) using the phenomenon of skip connections to eradicate the vanishing gradient problem and achieve a fast training process in recurrent networks. We also explore the concepts of XAI to improve trust level by providing explanations of the predictive decisions and enabling humans and security experts to understand the causal reasoning and underlying data evidence. The evaluation results on the ToN_IoT dataset demonstrate the effectiveness and superiority of the proposed XSRU-IoMT model as compared to the state-of-the-art compelling detection models, suggesting its usefulness as a viable deployment model in real-IoMT networks.

A quad-band metamaterial absorber operating in the terahertz region is demonstrated in this paper. The basic cell of the device consists of three metallic strips (forming an asymmetric I-type resonator) placed on both layers of an insulating medium slab and a metallic ground plane. The asymmetric I-type resonator can interact strongly with the incident beam, resulting in four distinct absorption peaks with nearly 100% absorbance. The underlying mechanism of the quad-band absorption is investigated with the aid of their near-field distributions resulting from the calculation results of the numerical simulation. Results further prove that the four distinct absorption peaks exhibit large dependence on the dimension changes of the asymmetric I-type resonator (or three metallic strips). Based on this, we design a kind of terahertz metamaterial absorber which can effectively control the number of absorption peaks by replacing one of the metallic strips with photosensitive silicon. It is revealed that the number of absorption peaks can be adjusted from the dual-band to the quad-band when an external stimulus changes the conductivity of the photosensitive silicon. These absorption properties should have great application prospects in terms of thermal imaging, Raman enhancement, sensing and detection, etc.

Brain electroencephalography (EEG), the complex, weak, multivariate, nonlinear, and nonstationary time series, has been recently widely applied in neurocognitive disorder diagnoses and brain-machine interface developments. With its specific features, unlabeled EEG is not well addressed by conventional unsupervised time-series learning methods. In this article, we handle the problem of unlabeled EEG time-series clustering and propose a novel EEG clustering algorithm, that we call mwcEEGc. The idea is to map the EEG clustering to the maximum-weight clique (MWC) searching in an improved Fréchet similarity-weighted EEG graph. The mwcEEGc considers the weights of both vertices and edges in the constructed EEG graph and clusters EEG based on their similarity weights instead of calculating the cluster centroids. To the best of our knowledge, it is the first attempt to cluster unlabeled EEG trials using MWC searching. The mwcEEGc achieves high-quality clusters with respect to intracluster compactness as well as intercluster scatter. We demonstrate the superiority of mwcEEGc over ten state-of-the-art unsupervised learning/clustering approaches by conducting detailed experimentations with the standard clustering validity criteria on 14 real-world brain EEG datasets. We also present that mwcEEGc satisfies the theoretical properties of clustering, such as richness, consistency, and order independence.

The present paper recognizes the pertinence of the monastic culture in the Hypnerotomachia Poliphili or Strife of Love in a Dream, written by Francesco Colonna in 1499. Taking as a starting point the hypothesis that the author was a Venetian monk, the research demonstrates the omnipresent Christian context in a novel that traditionally has been considered “pagan” and identifies the religious profession of the author projected over the protagonist (Poliphilo). Monastic codes of secret knowledge, prayer and meditation are content in a literary masterpiece, that reveals inner battles of the soul like distractions of the mind. Topics about free will and morality, and the recovery of human dignity, based on the role of the senses involved in the cognitive process are some of the conclusions that stem from the study of this novel from a Christian perspective.

In this work, we report high-performance amorphous indium gallium zinc oxide (a-IGZO) thin-film transistors (TFTs) with atomic layer deposited Al₂O₃ dielectric processed at a minimal temperature of 189.6 °C via microwave annealing (MWA). The a-IGZO TFT with MWA exhibits an improvement of 57% in subthreshold swing (SS) compared with the unannealed device; meanwhile, it retains high field-effect mobility of up to 29.2 cm²/(V · s) and large switching ratio of >10⁸. Moreover, the SS of the device was further reduced through a two-step MWA treatment. It is believed that MWA treatment effectively reduces the density of trap states associated with oxygen vacancies, promotes the formation of lattice oxygen, and thus improves the quality of IGZO film. MWA with low thermal budget shows great potential in applications of the back-end of line (BEOL)-compatible oxide devices.

Although autologous nerve transplantation is the gold standard for treating peripheral nerve defects, it has many clinical limitations. As an alternative, various tissue-engineered nerve grafts have been developed to substitute for autologous nerves. In this study, a novel nerve graft composed of chitin scaffolds and a small autologous nerve was used to repair sciatic nerve defects in rats. The novel nerve graft greatly facilitated regeneration of the sciatic nerve and myelin sheath, reduced atrophy of the target muscle, and effectively restored neurological function. When the epineurium of the small autogenous nerve was removed, the degree of nerve regeneration was similar to that which occurs after autogenous nerve transplantation. These findings suggest that our novel nerve graft might eventually be a new option for the construction of tissue-engineered nerve scaffolds. The study was approved by the Research Ethics Committee of Peking University People’s Hospital (approval No. 2019PHE27) on October 18, 2019.

Background Telemedicine helps to provide the safe management of stroke patients in the emergency department (ED) and has been used worldwide. However, we had limited experience of telestroke in Taiwan. We aimed to identify the quality of telestroke and compare it with the original face-to-face consultation model. Methods Among 178 consecutive acute ischemic stroke patients treated with intravenous tissue plasminogen activator (IVtPA) from January 1, 2018, to December 31, 2019, we compared two different consultation methods: face-to-face consultation and telestroke consultation. We collected data on demographics, the National Institutes of Health Stroke Scale (NIHSS) scores, Modified Rankin Scale (mRS) scores, time measurements (onset-to-arrival time, onset-to-telestroke activation time, and time of IVtPA administration (Door-to-Needle; DTN)). Results The mean age to receive a telestroke consultation was 66.6 years, 36% were female, and the median NIHSS score was 9. The median time from patient arrival to telestroke consult activation was 40 min, and the median DTN time was 11 min longer than for face-to-face consults (62 min versus 51 min, p = .01). Telestroke consultation, similar to a face-to-face consultation, resulted in safe IVtPA eligibility assessments and administration with post-thrombolysis ICH in 4% overall (4% telestroke, 3% face-to-face consultation; p = .851). The 90-day outcomes were not different for mRS score, dichotomized 0–2 (60% telestroke 59% face-to-face consultation; p = .961), or for mortality (16% telestroke, 9% face-to-face consultation; p = .292). Conclusion In the ED, consultation via the telestroke program provides equal quality to the original face-to-face consultation model to manage ischemic stroke.

Resumen: El melanoma desmoplásico (MD) representa entre el 0,4-4% de todos los melanomas. Se presenta como un tumor constituido predominantemente por melanocitos fusiformes amelanóticos inmersos en un estroma colágeno abundante. Se clasifica en MD puro o mixto, basándose en la proporción de melanoma desmoplásico frente a la del melanoma no desmoplásico presente en el tumor infiltrante. En el MD puro el componente desmoplásico representa más del 90% del melanoma infiltrante mientras que, en el MD combinado o mixto, el componente desmoplásico representa menos del 90%.El MD es más frecuente en varones (ratio 1,7-2:1); la edad media al diagnóstico oscila entre 66-69 años y suele localizarse en áreas de fotoexposición crónica, a menudo asociado a un lentigo maligno. Su reconocimiento clínico es difícil ya que se presenta como una pápula o placa no pigmentada, indurada y de bordes mal definidos, que recuerda a una cicatriz.El MD es un tumor con una alta tendencia a la recurrencia local y en el caso del MD puro, una baja tendencia a la diseminación ganglionar. Sin embargo, en las series más contemporáneas, su pronóstico global parece ser similar al de melanomas no desmoplásicos (MND) del mismo grosor. Su abordaje clínico posee algunos matices diferenciales, en comparación al resto de melanomas, que se revisan en el presente trabajo. Abstract: Desmoplastic melanoma (DM) accounts for 0.4% to 4% of all melanomas. These skin tumors are mainly formed by amelanotic spindled melanocytes immersed in an abundant collagen stroma and are classified as pure when the desmoplastic component accounts for at least 90% of the invasive tumor and as mixed or combined otherwise. DMs are more common in men (male to female ratio, 1.7 to 2:1), and the mean age at diagnosis is 66 to 69 years. The tumors tend to occur in chronically sun-exposed areas, often in association with lentigo maligna, and are difficult to recognize because they can resemble a scar, presenting as a firm, unpigmented papule or plaque with poorly defined borders. DMs also have a strong tendency to recur locally, and pure variants rarely spread to the lymph nodes. Nonetheless, recently published series suggest that patients with DM have a similar prognosis to those with nondesmoplastic melanoma of the same thickness. The clinical management of DM varies in certain aspects from that of other melanomas and is reviewed in this article.

A recent increase in screen time during early childhood has adversely affected the sleep and psychosocial health of children; however, limited information is available regarding effective interventions to reduce the screen time among them. This study aimed to investigate the effect of a parental educational program on screen use, sleep quality, and psychosocial adaptation among preschoolers.A clustered randomized controlled study with a parallel-group design was conducted. Preschoolers with a screen time of ≥2 h/day and their parents were recruited. In total, 14 kindergartens containing 129 parent-child dyads were randomly allocated to either the experimental group (receiving parental education, N = 63 dyads) or the control group (daily activities, N = 66 dyads). Data were collected before and after the intervention. A screen time questionnaire, the Children's Sleep Habits Questionnaire, and the Pediatric Symptom checklist-17 were provided to the participants. A linear mixed-model analysis was performed to examine the efficacy of the intervention.After the intervention, the screen time of children in the experimental group was significantly reduced (effect size: 0.83, p .001), and they presented improved sleep quality (effect size: 0.57, p = .01) and attention score (effect size: 0.77, p = .02) for psychosocial adaptation.Parental education is an effective intervention for reducing screen time and improving sleep quality and attention among preschoolers.Healthcare professionals should consider implementing parental educational programs to reduce screen time, and thus improve the sleep quality and psychosocial health of preschoolers.

Background: Vagus nerve stimulation (VNS) is used as an add-on treatment for epilepsy. This study aimed to use Taiwanese nationwide registry data to analyze the therapeutic effects of VNS in children with refractory epilepsy (RE) and try to explore predictive factors of VNS treatment effectiveness. Methods: This retrospective study collected data from December 2007 to December 2014. Patient variables included gender, age, VNS implantation date, epilepsy duration, seizure frequency, seizure type, etiology, and antiepileptic drug (AED) history. We divided patients into three groups: Group I as seizure frequency >80 times per month, Group II as seizure frequency 24–80 times per month, and Group III as seizure frequency

Titration of neuromuscular block (NMB) plays a key role in intraoperative recurrent laryngeal nerve monitoring during thyroid surgery. The combination of neuromuscular blocking agent and timely partial reversal of NMB was investigated in both animal experiments and clinical neuro-monitored thyroidectomy.In animal experiments, 8 piglets received sugammadex to assess the laryngeal EMG recovery after rocuronium-induced NMB. In clinical monitored thyroidectomy, 40 patients each were allocated to conventional group and sugammadex group. Conventional group received rocuronium 0.3 mg/kg at anesthesia induction, while sugammadex group received partial NMB recovery protocol- 0.6 mg/kg of rocuronium at anesthesia induction and 0.5 mg/kg of sugammadex. Main outcome was assessed by first (V1) and final (V2) EMG signal induced by vagal stimulation.In the porcine model, 50% recovery of laryngeal EMG amplitude was achieved at 16.8 ± 1.9 and 6 ± 2.7 minutes respectively after 0.5 and 1 mg/kg of sugammadex (Both porcine model and clinical application showed that precise NMB management by low-dose sugammadex was effective for intraoperative neural monitoring (IONM). The regimen ensured optimal conditions for tracheal intubation and timely neuromuscular function restoration for high-quality EMG signal.

Mode-locked lasers with low noise performance, such as low timing jitter and relative intensity noise are essential for high-precision applications. In this letter, we demonstrated a 122-MHz all-polarization-maintaining mode-locked Er-doped fiber laser based on a nonlinear amplifying loop mirror. A hybrid component integrating a wavelength division multiplexer and a phase shifter is applied to increase the repetition rate. The relative intensity noise is 0.004% and 0.76% rms (integrated from 1 MHz to 100 Hz) from two output ports. The timing jitter characteristic is measured by the delayed optical heterodyne method. The timing jitter is ~1.9 fs rms (integrated from 1 MHz to 10 Hz) of both two output ports. The origin of the timing jitter of this laser is analyzed numerically based on the well-established theoretical model using the laser’s repetition rate, cavity dispersion, etc.

Mechanistic target of rapamycin (mTOR) forms two distinct complexes, mTOR complex 1 (mTORC1) and mTORC2. Here we investigated the antitumor effect of dual mTORC1/2 inhibitor AZD2014 on epithelial ovarian cancer (EOC) and its potential effect on immunosuppressive myeloid-derived suppressor cells (MDSCs). Immunohistochemical analysis of mTORC1 and mTORC2 was performed on a human ovarian cancer tissue microarray. High mTORC2 expression level was associated with shorter survival in EOC, whereas mTORC1 was not correlate with patients’ prognosis. AZD2014 suppressed mTOR signaling pathway in ovarian cancer cells, inhibited proliferation and induced G1-phase cell cycle arrest and apoptosis. In tumor-bearing mice, AZD2014 treatment limited tumor growth, reduced peritoneal ascites, and prolonged survival. AZD2014 specifically reduced MDSCs migration and accumulation in EOC peritoneal fluid but not in the spleen. Moreover, subsequent AZD2014 treatment after cisplatin chemotherapy delayed EOC recurrence. Collectively, we observed that high mTORC2 expression level in EOC indicated a poor prognosis. Remarkably, in tumor-bearing mice, AZD2014 diminished MDSC accumulation and delayed tumor growth and recurrence.

3-Methylhistidine (3MH) is an indicator of muscle catabolism. Subclinical protein malnutrition is an independent predictor of aortic stiffness (AS). We aimed to study the relationship between serum 3MH level and AS among patients undergoing maintenance hemodialysis (MHD). Carotid-femoral pulse wave velocity was applied to measure AS of 110 MHD patients. Serum 3MH levels were analyzed using high-performance liquid chromatography and mass spectrometry. AS was defined as cfPWV >10 m/s. Forty-five (40.9%) patients were categorized as having AS. Multivariable logistic (odds ratio: 0.792, p

Colorectal cancer (CRC) is one of the main causes of cancer-related morbidity and mortality across the globe. Although serum biomarkers such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19–9 (CA-199) have been prevalently used as biomarkers in various cancers, they are neither very sensitive nor highly specific. Repeated tissue biopsies at different times of the disease can be uncomfortable for cancer patients. Additionally, the existence of tumor heterogeneity and the results of local biopsy provide limited information about the overall tumor biology. Against this backdrop, it is necessary to look for reliable and noninvasive biomarkers of CRC. Circulating tumor cells (CTCs), which depart from a primary tumor, enter the bloodstream, and imitate metastasis, have a great potential for precision medicine in patients with CRC. Various efficient CTC isolation platforms have been developed to capture and identify CTCs. The count of CTCs, as well as their biological characteristics and genomic heterogeneity, can be used for the early diagnosis, prognosis, and prediction of treatment response in CRC. This study reviewed the existing CTC isolation techniques and their applications in the clinical diagnosis and treatment of CRC. The study also presented their limitations and provided future research directions.

Skin cutaneous melanoma (SKCM) is one of the most destructive skin malignancies and has attracted worldwide attention. However, there is a lack of prognostic biomarkers, especially tumour microenvironment (TME)‐based prognostic biomarkers. Therefore, there is an urgent need to investigate the TME in SKCM, as well as to identify efficient biomarkers for the diagnosis and treatment of SKCM patients. A comprehensive analysis was performed using SKCM samples from The Cancer Genome Atlas and normal samples from Genotype‐Tissue Expression. TME scores were calculated using the ESTIMATE algorithm, and differential TME scores and differentially expressed prognostic genes were successively identified. We further identified more reliable prognostic genes via least absolute shrinkage and selection operator regression analysis and constructed a prognostic prediction model to predict overall survival. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy, and Cox regression analysis was applied to explore the relationship with clinicopathological characteristics. Finally, we identified a novel prognostic biomarker and conducted a functional enrichment analysis. After considering ESTIMATEScore and tumour purity as differential TME scores, we identified 34 differentially expressed prognostic genes. Using least absolute shrinkage and selection operator regression, we identified seven potential prognostic biomarkers (SLC13A5, RBM24, IGHV3OR16‐15, PRSS35, SLC7A10, IGHV1‐69D and IGHV2‐26). Combined with receiver operating characteristic and regression analyses, we determined PRSS35 as a novel TME‐based prognostic biomarker in SKCM, and functional analysis enriched immune‐related cells, functions and signalling pathways. Our study indicated that PRSS35 could act as a potential prognostic biomarker in SKCM by investigating the TME, so as to provide new ideas and insights for the clinical diagnosis and treatment of SKCM.

OBJECTIVE To determine whether metformin or lifestyle modification can lower rates of all-cause and cause-specific mortality in the Diabetes Prevention Program and Diabetes Prevention Program Outcomes Study. RESEARCH DESIGN AND METHODS From 1996 to 1999, 3,234 adults at high risk for type 2 diabetes were randomized to an intensive lifestyle intervention, masked metformin, or placebo. Placebo and lifestyle interventions stopped in 2001, and a modified lifestyle program was offered to everyone, but unmasked study metformin continued in those originally randomized. Causes of deaths through 31 December 2018 were adjudicated by blinded reviews. All-cause and cause-specific mortality hazard ratios (HRs) were estimated from Cox proportional hazards regression models and Fine-Gray models, respectively. RESULTS Over a median of 21 years (interquartile range 20–21), 453 participants died. Cancer was the leading cause of death (n = 170), followed by cardiovascular disease (n = 131). Compared with placebo, metformin did not influence mortality from all causes (HR 0.99 [95% CI 0.79, 1.25]), cancer (HR 1.04 [95% CI 0.72, 1.52]), or cardiovascular disease (HR 1.08 [95% CI 0.70, 1.66]). Similarly, lifestyle modification did not impact all-cause (HR 1.02 [95% CI 0.81, 1.28]), cancer (HR 1.07 [95% CI 0.74, 1.55]), or cardiovascular disease (HR 1.18 [95% CI 0.77, 1.81]) mortality. Analyses adjusted for diabetes status and duration, BMI, cumulative glycemic exposure, and cardiovascular risks yielded results similar to those for all-cause mortality. CONCLUSIONS Cancer was the leading cause of mortality among adults at high risk for type 2 diabetes. Although metformin and lifestyle modification prevented diabetes, neither strategy reduced all-cause, cancer, or cardiovascular mortality rates.

PurposeThe purpose of this study is to examine the determinants of career satisfaction of professional accounting returnees who have studied and/or worked abroad and then returned to work in different types of international workplaces in their home country.Design/methodology/approachA survey of professional accounting returnees in Vietnam was undertaken and multiple regression analysis was applied to test the proposed relationships.FindingsThis study finds that career satisfaction is affected by career fit, career sacrifice, types of international workplaces (domestically headquartered firms versus globally headquartered firms) and cross-cultural work readjustment. Further, cross-cultural work readjustment partially mediates the effect of career fit and career sacrifice on career satisfaction.Practical implicationsThe research provides the basis for designing career-related employee experiences to support career satisfaction of professional accounting returnees.Originality/valueThis study integrates dimensions of career embeddedness with cross-cultural work readjustment and employee experiences, which are normally studied separately, in different types of international workplaces. It contributes to the limited research on contributors to well-being in the form of career satisfaction among professional returnees in an emerging economy.

Current therapy does not provide significant benefits for patients with chronic stroke. Pre-clinical studies suggested that autologous adipose-derived stem cells have benefits for the treatment of chronic stroke. This Phase I open-label study was conducted to demonstrate the safety and efficacy of autologous adipose-derived stem cells (GXNPC1) in chronic stroke. Three patients with chronic stroke were treated with stereotactic implantation of autologous adipose-derived stem cells (1 × 108 cells). The primary endpoints of safety evaluation included adverse events, over a 6 months post-implantation period. The secondary endpoints included improvements in neurological functions. Evolutional change of brain parenchyma was also followed with magnetic resonance imaging (MRI). All three participants improved significantly at 6 months follow-up. The extent of improvement from pre-treatment was: National Institutes of Health Stroke Scale improved 5-15 points, Barthel Index: 25-50 points, Berg balance scale 0-21 points and Fugl-Meyer modified sensation 3-28 points. All three patients had signal change along the implantation tract on MRI one month after surgery. There is no related safety issue through 6 months observation. Clinical measures of neurological symptoms of these patients with chronic stroke improved at 6 months without adverse effects after implantation of autologous adipose-derived stem cells (GXNPC1), which might be correlated with post-implantation changes on brain MRI. Clinical Trial Registration-URL: https://clinicaltrials.gov/ct2/show/NCT02813512?term=ADSC&cond=Stroke&cntry=TW&draw=2&rank=1 Unique identifier: NCT02813512.

The resistance of urinary tract pathogenic bacteria to various antibiotics is increasing, which requires the rapid detection of infectious pathogens for accurate and timely antibiotic treatment. Here, we propose a rapid diagnosis strategy for the antibiotic resistance of bacteria in urinary tract infections (UTIs) based on surface-enhanced Raman scattering (SERS) using a positively charged gold nanoparticle planar solid SERS substrate. Then, an intelligent identification model for SERS spectra based on the deep learning technique is constructed to realize the rapid, ultrasensitive, and non-labeled detection of pathogenic bacteria. A total of 54,000 SERS spectra were collected from 18 isolates belonging to 6 species of common UTI bacteria in this work to realize identification of bacterial species, antibiotic sensitivity, and multidrug resistance (MDR) via convolutional neural networks (CNN). This method significantly simplify the Raman data processing processes without background removing and smoothing, however, achieving 96% above classification accuracy, which was significantly greater than the 85% accuracy of the traditional multivariate statistical analysis algorithm principal component analysis combined with the K-nearest neighbor (PCA-KNN). This work clearly elucidated the potential of combining SERS and deep learning technique to realize culture-free identification of pathogenic bacteria and their associated antibiotic sensitivity.

Heating, ventilation and air conditioning (HVAC) systems are widely used to regulate indoor temperature and air quality of modern buildings. The central supply and exhaust system cause the dispersal and removal of bioaerosols. This study presents results from ex situ experiments conducted to a better understanding of the spatiotemporal distribution, passive dispersal and removal of fungal spores through HVAC systems. The study was conducted in a 50 square meters by 3 m high instrument room in a research building with HVAC systems. Plates with Aspergillus flavus colony were attached upside down on the edge of the ceiling vent to imitate the mildew growing. Fungal spores were released for 10 min, collected and counted by the settle plate method in 2 h. Results show that A. flavus spores dispersed to 3.6 m in 2 min and were evenly distributed in the room within 8 min. The concentration of spores decreased from 48 to 3–6 CFU/plate after 60 min and was lower than 1% after 120 min. Our results suggest that airborne fungal spores disperse and remove by HVAC systems efficiently. Without the external and internal source, the HVAC system could greatly reduce the fungal amount in the indoor air to the background level within one hour. This study provided the observed data of the transmission and retention of internal or external biological contaminants through HVAC system.

Objective Clinical target volume (CTV) autosegmentation for cervical cancer is desirable for radiation therapy. Data heterogeneity and interobserver variability (IOV) limit the clinical adaptability of such methods. The adaptive method is proposed to improve the adaptability of CNN‐based autosegmentation of CTV contours in cervical cancer. Methods This study included 400 cervical cancer treatment planning cases with CTV delineated by radiation oncologists from three hospitals. The datasets were divided into five subdatasets (80 cases each). The cases in datasets 1, 2, and 3 were delineated by physicians A, B, and C, respectively. The cases in datasets 4 and 5 were delineated by multiple physicians. Dataset 1 was divided into training (50 cases), validation (10 cases), and testing (20 cases) cohorts, and they were used to construct the pretrained model. Datasets 2–5 were regarded as host datasets to evaluate the accuracy of the pretrained model. In the adaptive process, the pretrained model was fine‐tuned to measure improvements by gradually adding more training cases selected from the host datasets. The accuracy of the autosegmentation model on each host dataset was evaluated using the corresponding test cases. The Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD_95) were used to evaluate the accuracy. Results Before and after adaptive improvements, the average DSC values on the host datasets were 0.818 versus 0.882, 0.763 versus 0.810, 0.727 versus 0.772, and 0.679 versus 0.789, which are improvements of 7.82%, 6.16%, 6.19%, and 16.05%, respectively. The average HD_95 values were 11.143 mm versus 6.853 mm, 22.402 mm versus 14.076 mm, 28.145 mm versus 16.437 mm, and 33.034 mm versus 16.441 mm, which are improvements of 37.94%, 37.17%, 41.60%, and 50.23%, respectively. Conclusion The proposed method improved the adaptability of the CNN‐based autosegmentation model when applied to host datasets.

Background The antiviral resistance of cytomegalovirus (CMV) infections is associated with mutations in the CMV UL54 and UL97 gene regions and is a serious problem in immunocompromised patients. However, the molecular epidemiology of UL54 and UL97 in Taiwan is unclear. Methods We conducted a retrospective study of patients with CMV infections between January and December 2016 in two tertiary hospitals, one regional hospital in Taiwan. CMV DNAemia was confirmed by elevated CMV DNA titers. Then the regions of the UL54 and UL97 mutations were amplified by PCR and sequenced. Results Of 729 patients with CMV syndrome, 112 CMV DNAemia patients were enrolled. Twelve novel variants in UL54 (P342S, S384F, K434R, S673F, T754M, R778H, C814S, M827I, G878E, S880L, E888K, and S976N) and one novel variant in UL97 (M615T) were discovered. UL97 antiviral resistance mutations (L595S, M460I, and M460V) were found in four patients (3.6%). In the drug resistance strains, the mutation events occurred after 83–150 days of therapy, and drug resistance was also observed in these patients. The following high frequency variants were observed: D605E in UL97 and A885T, N898D, V355A, N685S, and A688V in UL54. Conclusion The results demonstrate that the positive rate of CMV DNAemia was 15.3% (112/729) among the patients with clinical CMV infection symptoms. The proportion of antiviral resistance CMV strains within CMV DNAemia patients was 3.6%. With the information of polymorphism incidence in the UL54 and UL97 patients from our study, determination of the genetic profile of UL54 and UL97 among immunocompromised populations with refractory CMV infection is recommended.

Objective The current study aimed to further verify the feasibility of ultrasound-guided selective pulsed radiofrequency (PRF) therapy of greater auricular nerve (GAN) in the treatment of head and neck post-herpetic neuralgia (PHN) by observing the efficacy and safety. Methods Under the guidance of high-frequency ultrasound (Frequency: 10 MHz), the GAN was identified by a radiofrequency electrode trocar with a transverse in-plane approach, which was inserted into the GAN, then the inner needle of the trocar was retracted. After adjusting the technical variables (electrode tip temperature: 42°C, output voltage: 60 V, pulse frequency: 2 Hz, pulse width: 22 ms, single duration: 240 s, two times), the radiofrequency electrode placed on the auricle and below the ear for sensory and motor tests began to work. Results The pain in the left head and neck of the patient lasted for more than 1 month, we decided to try selective PRF of GAN guided by ultrasound for the first time. Immediately after the treatment, 11-point pain intensity numerical rating scale (PI-NRS) score ranged from 5 to 1. During his hospitalization, mecobalamine and gabapentin were taken instead of opioids. Seven days after the procedure, PI-NRS score was 2, the degree of numbness the patient he felt by himself in the original lesion area relieved from 100% to 40%, the depression module of the Patient Health Questionnaire-9 (PHQ-9) score was from 7 to 5, the Generalized Anxiety Disorder-7 (GAD-7) score from 8 to 4, the range of pain areas was reduced to external auditory tract, and there were no adverse events occurring. Conclusion The ultrasound-guided selective PRF treatment of GAN was safe and effective in the improvement of PHN in the head and neck, which is worthy of clinical promotion.

Consensus criteria for tremor classification in Parkinson’s disease (PD) patients are clinically important for automatically evaluating the PD rating scale. Wearable sensing tools with direct contact measurements can obtain physiological signals to monitor tremor symptoms. Then, machine learning algorithms (MLAs) can train the frequency-based parameters and motion features to accurately measure PD-related tremors. Noncontact measurement with customized computer information devices can also digitalize the digitized handwritten patterns with the bespoke movements that a hand makes for identifying tremor classes. However, wearable sensors need a set of multiple electrodes to be placed on a patient’s body to acquire biosignals, and the setup does not allow continuous measurement and limits the patient’s motion range. The handwritten patterns of noncontact-based methods need frequency-domain and linearization transformations. In addition, feature extraction methods and MLAs are limited in complex computations and adaptive applications. Hence, in this work, a noncontact measurement with an array X-band microwave (10 GHz) Doppler-based linear quantizer is designed to continuously measure upper limb movements for tremor class scaling. To overcome the complex computations, time-domain parametric features, including zero crossing (ZC), Willison amplitude (WAMP), and waveform length (WL) indexes, are used to extract the physical changes in the oscillation frequencies, amplitudes, and directions of tremor signals for scaling upper limb tremor (ULT) levels. In the experiments involving 10 subjects, the proposed noncontact bioradar sensor could quantify asymmetrical and irregular oscillations with a positive correlation (mean R2 > 0.85) between the three indexes (ZC, WAMP, WL) and various oscillation frequencies. The linear relationship quantizer could predict the ULT levels from 0 Hz to 8 Hz for PD patients (typical tremor frequency: 4–6 Hz). It could also map the three indexes into colored visual representation for computerized visual analysis.

Background Unequal access to healthcare is a global medical problem. Telemedicine, recently made possible by technological advances, may mitigate this inequity. However, the usefulness of telemedicine for procedure-driven disciplines, such as otolaryngology, under infectious conditions (e.g., the COVID-19 pandemic) is unknown. Methods Telemedicine was made legal in Taiwan by an amendment to the Physician Act in 2018. Kaohsiung Chang Gung Memorial Hospital was the first hospital in Taiwan to provide the telemedicine service by connecting to the Chenggong Branch of Taitung Hospital (CGBTH) in November 2018. This retrospective cohort study included all new and established otolaryngology outpatient consultations between November 2018 and May 2020 at CGBTH. The Current Procedural Terminology and International Classification of Disease, 10th Revision codes, patient demographic data, and questionnaire data were obtained. Results The study included 123 patients with 218 encounters over 19 months. The majority of complaints were ear-related (52.6%). Overall, 49% of the encounters required a specialized procedure for diagnosis and treatment; of these, cerumen removal was the most common procedure. The patient subjective improvement rate increased over the study period (from 62.0% to 78.9%). The rates of return and case closure were both around 90% in 2018 and 2019. The number of otolaryngology consultations and rate of return declined after the start of the COVID-19 pandemic; however, the subjective improvement and case closure rates remained stable. The telemedicine service saved at least 2 h driving time per visit. Conclusion Telemedicine for otolaryngology is a promising approach for remote and underserved regions, as well as during an infectious disease pandemic.