A Survey on Service Route and Time Prediction in Instant Delivery: Taxonomy, Progress, and Prospects

Instant delivery services, such as food delivery and package delivery, have achieved explosive growth in recent years by providing customers with daily-life convenience. An emerging research area within these services is service Route\&Time Prediction (RTP), which aims to estimate the future service route as well as the arrival time of a given worker. As one of the most crucial tasks in those service platforms, RTP stands central to enhancing user satisfaction and trimming operational expenditures on these platforms. Despite a plethora of algorithms developed to date, there is no systematic, comprehensive survey to guide researchers in this domain. To fill this gap, our work presents the first comprehensive survey that methodically categorizes recent advances in service route and time prediction. We start by defining the RTP challenge and then delve into the metrics that are often employed. Following that, we scrutinize the existing RTP methodologies, presenting a novel taxonomy of them. We categorize these methods based on three criteria: (i) type of task, subdivided into only-route prediction, only-time prediction, and joint route\&time prediction; (ii) model architecture, which encompasses sequence-based and graph-based models; and (iii) learning paradigm, including Supervised Learning (SL) and Deep Reinforcement Learning (DRL). Conclusively, we highlight the limitations of current research and suggest prospective avenues. We believe that the taxonomy, progress, and prospects introduced in this paper can significantly promote the development of this field

Direct observation of layer-stacking and oriented wrinkles in multilayer hexagonal boron nitride

Hexagonal boron nitride (h-BN) has long been recognized as an ideal substrate for electronic devices due to its dangling-bond-free surface, insulating nature and thermal/chemical stability. Therefore, to analyse the lattice structure and orientation of h-BN crystals becomes important. Here, the stacking order and wrinkles of h-BN are investigated by transmission electron microscopy (TEM). It is experimentally confirmed that the layers in the h-BN flakes are arranged in the AA' stacking. The wrinkles in a form of threefold network throughout the h-BN crystal are oriented along the armchair direction, and their formation mechanism was further explored by molecular dynamics simulations. Our findings provide a deep insight about the microstructure of h-BN and shed light on the structural design/electronic modulations of two-dimensional crystals.Comment: 7 pages, 5 figure

A new variance-based approach for discriminative feature extraction in machine hearing classification using spectrogram features

Machine hearing is an emerging research field that is analogous to machine vision in that it aims to equip computers with the ability to hear and recognise a variety of sounds. It is a key enabler of natural human–computer speech interfacing, as well as in areas such as automated security surveillance, environmental monitoring, smart homes/buildings/cities. Recent advances in machine learning allow current systems to accurately recognise a diverse range of sounds under controlled conditions. However doing so in real-world noisy conditions remains a challenging task. Several front–end feature extraction methods have been used for machine hearing, employing speech recognition features like MFCC and PLP, as well as image-like features such as AIM and SIF. The best choice of feature is found to be dependent upon the noise environment and machine learning techniques used. Machine learning methods such as deep neural networks have been shown capable of inferring discriminative classification rules from less structured front–end features in related domains. In the machine hearing field, spectrogram image features have recently shown good performance for noise-corrupted classification using deep neural networks. However there are many methods of extracting features from spectrograms. This paper explores a novel data-driven feature extraction method that uses variance-based criteria to define spectral pooling of features from spectrograms. The proposed method, based on maximising the pooled spectral variance of foreground and background sound models, is shown to achieve very good performance for robust classification

Uniportal Subcostal Video-Assisted Thoracoscopic Surgery: A Feasible Approach for a Challenging Middle Lobectomy in an Obese Patient

Subcostal access is a novel approach for anatomical lung resection. To perform surgery via this access, specially designed long instruments are required. Subcostal access provides excellent visualization of the mediastinum and anterior lung hilum. We exhibit here a subcostal middle lobectomy with systematic en-block mediastinal lymphadenectomy in an obese 52-year-old male patient with body mass index (BMI=37.7) performed via this single incision. The operation was completed efficiently within 30 minutes with negligible postoperative pain

Analysis of special technical problems of wireless charging at UUV docking stations and a new underwater electromagnetic coupler

In order to solve the problem of insufficient range of autonomous underwater vehicles, underwater docking stations deployed on the seabed can wirelessly charge autonomous underwater vehicles through recyclers. Compared with traditional wireless charging of electric vehicles, wireless charging based on underwater docking stations has many special technical problems that need to be further understood and deciphered. This paper introduces the basic functions of the docking system and the docking process, and then focuses on the following three aspects of wireless charging at docking stations: firstly, the design of the coupler to suit the underwater vehicle and the complex marine environment, the coupler mechanism should match the shape and structure of the underwater vehicle, and the coupler should have a high resistance to deflection; secondly, the influence of the seawater medium on the wireless charging system. The impact of seawater medium on the wireless charging system is analysed, and the equivalent circuit model considering seawater eddy currents and the equivalent circuit model considering cross-connecting capacitance effects are established respectively; thirdly, the design of communication-independent wireless charging system. The existing eddy current loss calculation methods are analysed for the key technical problem of eddy current loss in seawater. A new type of electromagnetic coupler is proposed, the structural characteristics of the coupler are introduced and the simulation results show that the new coupler has a strong anti-deflection capability

Correction: Ji et al. Mesoporous Cobalt Oxide (CoO_x) Nanowires with Different Aspect Ratios for High Performance Hybrid Supercapacitors. <i>Nanomaterials</i> 2023, <i>13</i>, 749

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Mesoporous Cobalt Oxide (CoO_x) Nanowires with Different Aspect Ratios for High Performance Hybrid Supercapacitors

Cobalt oxide (CoOx) nanowires have been broadly explored as advanced pseudocapacitive materials owing to their impressive theoretical gravimetric capacity. However, the traditional method of compositing with conductive nanoparticles to improve their poor conductivity will unpredictably lead to a decrease in actual capacity. The amelioration of the aspect ratio of the CoOx nanowires may affect the pathway of electron conduction and ion diffusion, thereby improving the electrochemical performances. Here, CoOx nanowires with various aspect ratios were synthesized by controlling hydrothermal temperature, and the CoOx electrodes achieve a high gravimetric specific capacity (1424.8 C g−1) and rate performance (38% retention at 100 A g−1 compared to 1 A g−1). Hybrid supercapacitors (HSCs) based on activated carbon anode reach an exceptional specific energy of 61.8 Wh kg−1 and excellent cyclic performance (92.72% retention, 5000 cycles at 5 A g−1). The CoOx nanowires exhibit great promise as a favorable cathode material in the field of high-performance supercapacitors (SCs)

Uniportal video-assisted versus open pneumonectomy: a propensity score-matched comparative analysis with short-term outcomes

Objectives Uniportal (U-VATS) pneumonectomy in lung cancer patients remains disputed in terms of oncological outcomes, and has not been compared to open approaches previously. We evaluated U-VATS versus open pneumonectomy at a high-volume centre. Methods Patients undergoing pneumonectomy for lung cancer between 2014 and 2018 were retrospectively reviewed and divided into two groups based on surgical approach. Propensity-score matching was performed (1:1), and intention-to-treat analysis applied. Overall survival, operative time, intraoperative blood loss, hospital-stay and readmission, pain, time to adjuvant therapy, morbidity and mortality were tested. Statistical analysis was performed using SAS version 9.4 (SAS Institute Inc. NC) Results 341 patients underwent pneumonectomy; 23 patients with small-cell lung cancer were excluded, thus 318 patients were submitted to surgery by either U-VATS (n = 54) or open (n = 264). After matching, 52 patients were selected from each group. Five patients (9.2%) in the uniportal group required conversion. There was no significant difference in intraoperative outcomes, complication rates, readmission rates or mortality. The U-VATS group experienced significantly shorter hospital stay (mean +/- SD; 6.7 +/- 2.7 vs 9.1 +/- 2.3 days, p &lt; 0.001) and reported less pain postoperatively (p &lt; 0.0001). Adjuvant chemotherapy was initiated sooner after U-VATS (38.1 +/- 8.4 vs 50.8 +/- 11.5 days, p &lt; 0.0001). Overall survival appeared to be superior in U-VATS when pathology stage was aligned (p = 0.001). Conclusions Uniportal VATS is a safe and effective alternative approach to open surgery for pneumonectomy in lung cancer. Complications and oncologic outcomes were comparatively similar. U-VATS showed lower postoperative pain, shorter hospital stay and superior overall survival. The study is a preliminary analysis