Miracle-dz/UniFAR-FTUs huggingface dataset:
Management of stage I occult uterine leiomyosarcoma: effects of morcellation, second-look surgery, and adjuvant treatments on survival

Background This study sought to analyze the risk of morcellation in patients who underwent surgery for leiomyoma and had a final pathological diagnosis of uterine leiomyosarcoma (uLMS), and evaluate the survival benefits of second-look surgery and chemotherapy in patients with stage I occult uLMS. Methods A retrospective analysis of the data of patients with occult stage I uLMS in the Peking Union Medical College Hospital database between 2005 and 2018 was conducted. The recurrence rate and progression-free survival (PFS) were compared between patients who underwent morcellation or not. Univariate analyses were used to evaluate the survival impact of lymphadenectomy, oophorectomy and adjuvant chemotherapy. Propensity-score matching methods were used to evaluate the effect of morcellation on recurrence while adjusting for baseline confounding factors using Poisson regression fitted by inverse probability weighting (IPW) estimation. Results A total of 96 patients with uLMS were identified among the 31,679 surgeries performed for leiomyomas (incidence: 0.303%). Hysterectomy was performed in 60 patients, and myomectomy was performed in 36 patients (power morcellation n=20). There were 36 (37.5%) patients underwent lymphadenectomy, and 76 (79.2%) patients underwent oophorectomy. Among them, 47 (52.8%) patients received postoperative chemotherapy. The median follow-up time was 40 months (range, 12–146 months), and there were 43 cases of recurrence (44.7%). No differences in recurrence were found between the hysterectomy and myomectomy groups (hazard ratio 0.839, P=0.701). The 3-year PFS rates for patients with hysterectomy, power morcellation, and non-power morcellation were 64.3%, 53.8%, and 59.8%, respectively. No survival differences were identified between patients with/without lymphadenectomy [PFS: P=0.513; overall survival (OS): P=0.413] and oophorectomy (PFS: P=0.162; OS: P=0.815). Postoperative chemotherapy was associated with better PFS (P=0.047), but not OS (P=0.36). Conclusions No survival differences were observed among the initial surgical procedures in stage I patients with occult uLMS. No survival benefits were observed between lymphadenectomy and oophorectomy patients. Compared to continued observation, postoperative chemotherapy was associated with improved PFS, but not OS.
Propylene Glycol Caprylate-Based Nanoemulsion Formulation of Plumbagin: Development and Characterization of Anticancer Activity

Plumbagin, a bioactive naphthoquinone, has demonstrated potent antitumor potential. However, plumbagin is a sparingly water-soluble compound; therefore, clinical translation requires and will be facilitated by the development of a new pharmaceutical formulation. We have generated an oil-in-water nanoemulsion formulation of plumbagin using a low-energy spontaneous emulsification process with propylene glycol caprylate (Capryol 90) as an oil phase and Labrasol/Kolliphor RH40 as surfactant and cosurfactant excipients. Formulation studies using Capryol 90/Labrasol/Kolliphor RH40 components, based on pseudoternary diagram and analysis of particle size distribution and polydispersity determined by dynamic light scattering (DLS), identified an optimized composition of excipients for nanoparticle formulation. The nanoemulsion loaded with plumbagin as an active pharmaceutical ingredient had an average hydrodynamic diameter of 30.9 nm with narrow polydispersity. The nanoemulsion exhibited long-term stability, as well as good retention of particle size in simulated physiological environments. Furthermore, plumbagin-loaded nanoemulsion showed an augmented cytotoxicity against prostate cancer cells PTEN-P2 in comparison to free drug. In conclusion, we generated a formulation of plumbagin with high loading drug capacity, robust stability, and scalable production. Novel Capryol 90-based nanoemulsion formulation of plumbagin demonstrated antiproliferative activity against prostate cancer cells, warranting thus further pharmaceutical development.
Fault-tolerant structure for cascaded H-bridge multilevel inverter and reliability evaluation

In this study, a fault-tolerant structure and its controlling method for a cascaded H-bridge multilevel inverter is introduced. When a fault occurs in one of the modules, the proposed circuit is able to isolate and eliminate the defective module from the whole system. The isolation and elimination is done by four relays in each module and a controlling circuit. This solution makes the system continue the normal operation by means of the remained healthy modules with decreased output voltage level. Therefore, the whole system failure will be prevented and higher reliability of the inverter will be guaranteed. Principles of operation and the controlling method are presented in this study. Reliability evaluation and comparison of the proposed fault-tolerant structure and the conventional one are considered. To ensure the correct performance of the proposed cascaded H-bridge multilevel inverter, a prototype has been synthesised in the laboratory. The obtained results affirm higher reliability and mean time to failure of the proposed circuit, so suitability of the proposed structure for sensitive industrial applications is confirmed.
First record of the family Issidae (Hemiptera, Auchenorrhyncha, Fulgoroidea) from the Hawaiian Islands

Abstract Background Euroxenusvayssieresi (Bonfils, Attie & Reynaud, 2001) (Issinae, Sarimini) was described (in the genus Borbonissus Bonfils, Attie & Reynaud, 2001) from Réunion Island, in the Indian Ocean and, previous to this report, has not been recorded elsewhere. Euroxenusvayssieresi is here illustrated and re-described to improved taxonomic diagnosis. New information Euroxenusvayssieresi is recorded for the first time from the Island of Hawaii in the Hawaiian Archipelago. This is first record of the family Issidae from the Hawaiian Archipelago.
Image-Aided LiDAR Mapping Platform and Data Processing Strategy for Stockpile Volume Estimation

Stockpile quantity monitoring is vital for agencies and businesses to maintain inventory of bulk material such as salt, sand, aggregate, lime, and many other materials commonly used in agriculture, highways, and industrial applications. Traditional approaches for volumetric assessment of bulk material stockpiles, e.g., truckload counting, are inaccurate and prone to cumulative errors over long time. Modern aerial and terrestrial remote sensing platforms equipped with camera and/or light detection and ranging (LiDAR) units have been increasingly popular for conducting high-fidelity geometric measurements. Current use of these sensing technologies for stockpile volume estimation is impacted by environmental conditions such as lack of global navigation satellite system (GNSS) signals, poor lighting, and/or featureless surfaces. This study addresses these limitations through a new mapping platform denoted as Stockpile Monitoring and Reporting Technology (SMART), which is designed and integrated as a time-efficient, cost-effective stockpile monitoring solution. The novel mapping framework is realized through camera and LiDAR data-fusion that facilitates stockpile volume estimation in challenging environmental conditions. LiDAR point clouds are derived through a sequence of data collections from different scans. In order to handle the sparse nature of the collected data at a given scan, an automated image-aided LiDAR coarse registration technique is developed followed by a new segmentation approach to derive features, which are used for fine registration. The resulting 3D point cloud is subsequently used for accurate volume estimation. Field surveys were conducted on stockpiles of varying size and shape complexity. Independent assessment of stockpile volume using terrestrial laser scanners (TLS) shows that the developed framework had close to 1% relative error.
A Genetic Algorithm based Hybrid Deep Learning Approach for Heart Disease
Prediction

People nowadays suffer from a variety of heart ailments as a result of the environment and their lifestyle choices. As a result, analyzing sickness at an early stage becomes a critical responsibility. Data mining uses disease data to uncover important knowledge. In this research paper, we employ the hybrid combination of a Genetic Algorithm based Feature selection and Ensemble Deep Neural Network Model for Heart Disease prediction. In this algorithm, we used a 0.04 learning rate and Adam optimizer was used for enhancement of the proposed model. The proposed algorithm has come to 98% accuracy of heart disease prediction, which is higher than the past approaches. Other exist models such as random forest, logistic regression, support vector machine, Decision tree algorithms have taken a higher time and give less accuracy compare to the proposed hybrid deep learning-based approach.
A system for collecting emotionally annotated physiological signals in daily life using wearables

Several obstacles have to be overcome in order to recognize emotions and affect in daily life. One of them is collecting a large amount of emotionally annotated data necessary to create data-greedy machine learning-based predictive models. Hence, we propose the Emognition system supporting the collection of rich emotional samples in everyday-life scenarios. The system utilizes smart-wearables to record physiological signals unobtrusively and smartphones to gather self-assessments. We have performed a two-week pilot study with 15 participants and devices available on the market to validate the system. The outcomes of the study, alongside the discussion and lessons learned, are provided.
Data Relevance-Aware Dynamic Sensing Technique with Battery Lifetime Guarantee for Wireless Sensor Nodes

Significant effort has been devoted to the development of dynamic monitoring techniques to exploit the temporal correlation among observations with the intention of improving the energy efficiency in wireless sensor nodes. However, the unpredictable nature of these approaches can also be a drawback for their adoption in safety-critical applications. For battery-powered sensor nodes, the predictability of the battery lifetime of the node is paramount for their correct maintenance and operation. Nevertheless, little effort has been made to provide some level of predictability in the available dynamic sampling techniques. The work presented in this article aims to solve this problem by proposing a dynamic monitoring method, capable of exploiting temporal correlation, to improve its energy usage, while at the same time being able to comply with the battery lifetime constraints. The initial evaluation tests show that the proposed sampling method is able to outperform traditional non-adaptive sampling approaches in terms of energy usage, while being able to achieve its battery lifetime goals, even in the presence of disturbances in the energy consumption of the sensor node.
Diagnosing Fungal Keratitis and Simultaneously Identifying Fusarium and Aspergillus Keratitis with a Dot Hybridization Array

Fungal keratitis (FK) is one of the most common microbial keratitis, which often leads to poor prognosis as a result of delayed diagnosis. Several studies implied that early differentiation of the two major FK, Fusarium and Aspergillus keratitis, could be helpful in selecting effective anti-fungal regimens. Therefore, a novel dot hybridization array (DHA) was developed to diagnose FK and differentiate Fusarium and Aspergillus keratitis in this study. One hundred forty-six corneal scrapes obtained from one hundred forty-six subjects impressed with clinically suspected FK were used to evaluate the performance of the DHA. Among these patients, 107 (73.3%) patients had actual FK confirmed by culture and DNA sequencing. We found that the DHA had 93.5% sensitivity and 97.4% specificity in diagnosing FK. In addition, this array had 93.2% sensitivity and 93.8% specificity in diagnosing Fusarium keratitis, as well as 83.3% sensitivity and 100% specificity in diagnosing Aspergillus keratitis. Furthermore, it had 83.9% sensitivity and 100% specificity in identifying Fusarium solani keratitis. Thus, this newly developed DHA will be beneficial to earlier diagnosis, more precise treatment, and improve prognosis of FK, by minimizing medical refractory events and surgical needs.
Ab-initio simulation of hydrogenated graphene properties

Ab-initio simulation of hydrogenated graphene properties was performed. At present, graphene is considered one of the most promising materials for the formation of new semiconductor devices with good characteristics. Graphene has been the subject of many recent investigations due to its peculiar transport, mechanical and others properties [1]. The chemical modification of graphene named as graphane has recently entered the investigation as a possible candidate to solve problems connected with the lack of a graphene bandgap. Graphane is a compound material consisting of two-dimensional graphene bonded by some atoms of hydrogen. The investigation shows that graphane has the three valley Г-М-K band structure with the Г valley, which has the smallest energy gap between the conductivity zone and the valence zone. The calculation of relative electron masses and non-parabolic coefficients in Г, М and K valleys was performed. Based on the obtained characteristics, it is possible to implement a statistical multi-particle Monte Carlo method to determine the characteristics of electron transfer in heterostructure semiconductor devices. A research on modified graphene structures is important for fundamental science and technological applications in high-speed transistor structures operating in the microwave and very high frequency ranges.
Influence of Etching Trench on Keff2 of Film Bulk Acoustic Resonator

As radio-frequency (RF) communication becomes more ubiquitous globally, film bulk acoustic resonators (FBAR) have attracted great attention for their superior performance. One of the key parameters of an FBAR, the effective electromechanical coupling coefficient (Keff2), has a great influence on the bandwidth of RF filters. In this work, we propose a feasible method to tune the Keff2 of the FBAR by etching the piezoelectric material to form a trench around the active area of the FBAR. The influence of the position of the etching trench on the Keff2 of the FBAR was investigated by 3D finite element modeling and experimental fabricating. Meanwhile, a theoretical electrical model was presented to test and verify the simulated and measured results. The Keff2 of the FBAR tended to be reduced when the distance between the edge of the top electrode and the edge of the trench was increased, but the Q value of the FBAR was not degraded. This work provides a new possibility for tuning the Keff2 of resonators to meet the requirements of different filter bandwidths.
A Compact Lithium-Ion Battery Charger for Low-Power Applications

In this brief, a linear-based battery charger is proposed, designed, fabricated in a 180 nm SOI process, and measured. The design is aimed to charge low-power wearable or implantable medical devices through a wireless power transfer (WPT) link at a transfer distance of several centimeters, where the available power is in the range of a few milliwatts. A novel self-turn-on/off circuit was implemented, preventing quiescent power consumption while the WPT link is inactive. The compact proposed circuit requires a remarkable low chip area of 0.023 mm2. In measurements, using a 3.7 V (nominal) lithium-Ion battery, a configurable charging current from 500 $\mu \text{A}$ to 20 mA was achieved, while presenting a competitive efficiency with the state-of-the-art. The automatic transition between the constant current (CC) and constant voltage (CV) charging phases is shown in measurements.
Rhynchosia volubilis Promotes Cell Survival via cAMP-PKA/ERK-CREB Pathway

Rhynchosia volubilis, a small black bean, has been used as a traditional remedy to treat diseases and maintain health in East Asia, but its cellular effects and molecular mechanisms are not fully understood. The purpose of this study was to investigate the effect of ethanol extract from Rhynchosia volubilis (EERV) on cell survival and to elucidate the biochemical signaling pathways. Our results showed that EERV stimulated the cyclic AMP (cAMP) signal revealed by a fluorescent protein (FP)-based intensiometric sensor. Using a Förster resonance energy transfer (FRET)-based sensor, we further revealed that EERV could activate PKA and ERK signals, which are downstream effectors of cAMP. In addition, we reported that EERV could induce the phosphorylation of CREB, a key signal for cell survival. Thus, our results suggested that EERV protects against apoptosis by activating the cell survival pathway through the cAMP-PKA/ERK-CREB pathway.
A Demand-Side Response-Based Transmission Planning Model With Grid-Connected Wind Farms

Leading the demand-side response mechanism into transmission planning can impel consumers to change their behavior in electricity consumption according to real-time power supply conditions,and it is favorable to improve the flexibility of power network operation and is also an effective manner to cope with the uncertainty due to grid-connected wind farms.Synthetically considering the uncertainty of wind power generation sets,an estimation model of wind power output is built,and leading demand-side response cost into the objective function of transmission planning,a transmission planning model based on demand-side response is established and solved by greedy randomized adaptive search procedure(GRASP). The results of measuring the proposed transmission planning model based on demand-side response by Garver 6-bus and IEEE 24-bus system show that the proposed model is effective.
Accumulation of Anthocyanidins Determines Leaf Color of Liquidambar Formosana as Revealed by Transcriptome Sequencing and Metabolism Analysis

Liquidambar formosana is important for its ornamental value in China; it is increasingly used for landscaping and gardening trees due to its diverse leaf colors and seasonal changes. Varieties including either a fixed leaf color, the purplish ‘Fuluzifeng’ (ZF), or seasonal changes in leaf color, the reddish ‘Nanlinhong’ (NLH) have been bred and registered as new plant varieties under the International Union for the Protection of New Plant Varieties (UPOV) system. To gain practical insights into the anthocyanin biosynthetic process, transcriptome sequencing (Illumina) was performed to clarify the metabolic pathways present in the three seasonal changes in leaf colors in NLH and in the springtime purple-red color of ZF. qRT-PCR was used to verify the speculation. Based on the differentially expressed genes and flavonoids analyses, the spring, summer, and autumn leaves of NLH were compared to study the seasonal differences. NLH and ZF were compared to study the formation mechanism of the two leaf colors in spring. Transcriptome sequencing produced a total of 121,216 unigenes from all samples, where 48 unigenes were differentially expressed and associated with the anthocyanidin pathway. The expression levels of LfDFR and LfANS genes corresponded to the accumulation of concentrations of cyanidins in spring (NLHC) and autumn leaves (NLHQ), respectively, with different shades of red. Moreover, the LfF3′5′H gene corresponded to the accumulation of flavonols and delphinidins in purple-red leaves (ZFC). Cyanidin and peonidin were the key pigments in red and dark-red leaves, and purple-red leaves were co-pigmented by cyanidins, pelargonidins, and delphinidins.
MaDoPO: Magnetic Detection of Positions and Orientations of Segmented Deep Brain Stimulation Electrodes: A Radiation-Free Method Based on Magnetoencephalography

Background: Current approaches to detect the positions and orientations of directional deep brain stimulation (DBS) electrodes rely on radiative imaging data. In this study, we aim to present an improved version of a radiation-free method for magnetic detection of the position and the orientation (MaDoPO) of directional electrodes based on a series of magnetoencephalography (MEG) measurements and a possible future solution for optimized results using emerging on-scalp MEG systems. Methods: A directional DBS system was positioned into a realistic head–torso phantom and placed in the MEG scanner. A total of 24 measurements of 180 s each were performed with different predefined electrode configurations. Finite element modeling and model fitting were used to determine the position and orientation of the electrode in the phantom. Related measurements were fitted simultaneously, constraining solutions to the a priori known geometry of the electrode. Results were compared with the results of the high-quality CT imaging of the phantom. Results: The accuracy in electrode localization and orientation detection depended on the number of combined measurements. The localization error was minimized to 2.02 mm by considering six measurements with different non-directional bipolar electrode configurations. Another six measurements with directional bipolar stimulations minimized the orientation error to 4°. These values are mainly limited due to the spatial resolution of the MEG. Moreover, accuracies were investigated as a function of measurement time, number of sensors, and measurement direction of the sensors in order to define an optimized MEG device for this application. Conclusion: Although MEG introduces inaccuracies in the detection of the position and orientation of the electrode, these can be accepted when evaluating the benefits of a radiation-free method. Inaccuracies can be further reduced by the use of on-scalp MEG sensor arrays, which may find their way into clinics in the foreseeable future.
Counteracting Selfish Nodes Using Reputation Based System in Mobile Ad Hoc Networks

A mobile ad hoc network (MANET) is a group of nodes constituting a network of mobile nodes without predefined and pre-established architecture where mobile nodes can communicate without any dedicated access points or base stations. In MANETs, a node may act as a host as well as a router. Nodes in the network can send and receive packets through intermediate nodes. However, the existence of malicious and selfish nodes in MANETs severely degrades network performance. The identification of such nodes in the network and their isolation from the network is a challenging problem. Therefore, in this paper, a simple reputation-based scheme is proposed which uses the consumption and contribution information for selfish node detection and cooperation enforcement. Nodes failing to cooperate are detached from the network to save resources of other nodes with good reputation. The simulation results show that our proposed scheme outperforms the benchmark scheme in terms of NRL (normalized routing load), PDF (packet delivery fraction), and packet drop in the presence of malicious and selfish attacks. Furthermore, our scheme identifies the selfish nodes quickly and accurately as compared to the benchmark scheme.