High-Performance Nanofluidic Osmotic Power Generation Enabled by Exterior Surface Charges under the Natural Salt Gradient

High-performance osmotic energy conversion (OEC) requires both high ionic selectivity and permeability in nanopores. Here, through systematical explorations of influences from individual charged nanopore surfaces on the performance of OEC, we find that the charged exterior surface on the low-concentration side (surfaceL) is essential to achieve high-performance osmotic power generation, which can significantly improve the ionic selectivity and permeability simultaneously. Detailed investigation of ionic transport indicates that electric double layers near charged surfaces provide high-speed passages for counterions. The charged surfaceL enhances cation diffusion through enlarging the effective diffusive area, and inhibits anion transport by electrostatic repulsion. Different areas of charged exterior surfaces have been considered to mimic membranes with different porosities in practical applications. Through adjusting the width of the charged ring region on the surfaceL, electric power in single nanopores increases from 0.3 to 3.4 pW with a plateau at the width of ~200 nm. The power density increases from 4200 to 4900 W/m2 and then decreases monotonously that reaches the commercial benchmark at the charged width of ~480 nm. While, energy conversion efficiency can be promoted from 4% to 26%. Our results provide useful guide in the design of nanoporous membranes for high-performance osmotic energy harvesting.Comment: 30 pages and 7 figure

Enhancing Generalizable 6D Pose Tracking of an In-Hand Object with Tactile Sensing

While holding and manipulating an object, humans track the object states through vision and touch so as to achieve complex tasks. However, nowadays the majority of robot research perceives object states just from visual signals, hugely limiting the robotic manipulation abilities. This work presents a tactile-enhanced generalizable 6D pose tracking design named TEG-Track to track previously unseen in-hand objects. TEG-Track extracts tactile kinematic cues of an in-hand object from consecutive tactile sensing signals. Such cues are incorporated into a geometric-kinematic optimization scheme to enhance existing generalizable visual trackers. To test our method in real scenarios and enable future studies on generalizable visual-tactile tracking, we collect a real visual-tactile in-hand object pose tracking dataset. Experiments show that TEG-Track significantly improves state-of-the-art generalizable 6D pose trackers in both synthetic and real cases

Unified Physical-Digital Face Attack Detection

Face Recognition (FR) systems can suffer from physical (i.e., print photo) and digital (i.e., DeepFake) attacks. However, previous related work rarely considers both situations at the same time. This implies the deployment of multiple models and thus more computational burden. The main reasons for this lack of an integrated model are caused by two factors: (1) The lack of a dataset including both physical and digital attacks with ID consistency which means the same ID covers the real face and all attack types; (2) Given the large intra-class variance between these two attacks, it is difficult to learn a compact feature space to detect both attacks simultaneously. To address these issues, we collect a Unified physical-digital Attack dataset, called UniAttackData. The dataset consists of $1,800$ participations of 2 and 12 physical and digital attacks, respectively, resulting in a total of 29,706 videos. Then, we propose a Unified Attack Detection framework based on Vision-Language Models (VLMs), namely UniAttackDetection, which includes three main modules: the Teacher-Student Prompts (TSP) module, focused on acquiring unified and specific knowledge respectively; the Unified Knowledge Mining (UKM) module, designed to capture a comprehensive feature space; and the Sample-Level Prompt Interaction (SLPI) module, aimed at grasping sample-level semantics. These three modules seamlessly form a robust unified attack detection framework. Extensive experiments on UniAttackData and three other datasets demonstrate the superiority of our approach for unified face attack detection.Comment: 12 pages, 8 figure

From Waterloo to the Great Wall: A retrospective, multicenter study on the clinical practice and cultural attitudes in the management of premature ejaculation, in China

Premature ejaculation (PE), despite its wide prevalence, is largely underdiagnosed and undertreated. Being a multifactorial dysfunction with strong cultural characteristics, PE requires skillful attitudes in the psychosexological support, necessary to manage the patient's and the couple's expectations, as well as in the medical treatment. Dapoxetine is a short-acting selective serotonin reuptake inhibitor approved for use in lifelong and acquired PE in a number of countries. Opinions, not always generated by the evidence-based medicine, impacted the attitudes of Western andrologists, as a nocebo effect which produced a drug's Waterloo, characterized by low prescription rates much more built on the patients' and doctors' expectations than on costs, side effects, and efficacy.In the present study, we retrospectively reviewed real-life data from eight Andrology and Sexual Medicine Public Centers in China to assess the prevalence of PE among attending patients, its association with erectile dysfunction, its subtype, and the proposed treatments. In 2019, among 156,486 patients coming to the centers, 32,667 visits having PE as the chief complaint were performed (20.9%). Almost all patients received treatment prescriptions (32,641 patients, 99.92%); 23,273 patients came back for a follow-up visit in the subsequent 12 months (71.2% of those who initially received treatment). Dapoxetine, either alone or in combination with another therapy, was the most prevalent treatment, prescribed to 22,767 patients (69.7% of treated patients), followed by traditional Chinese medicine (TCM) (39.4%). At follow-up, 8174 patients were unsatisfied with treatment, and a new treatment was proposed (35.12%). Dapoxetine was the best treatment, with an overall 27.1% switching rate when used either alone or in combination: Although the switching rate for Dapoxetine alone was 44.2%, the association of the same drug with psychotherapy resulted in much lower rates (19.5%) and reached a minimum of 12% when also combined with TCM demonstrating how cultural aspects and medical attitudes may dramatically impact on the therapy of a multifaceted, complex, and culture-grounded sexual symptom such as PE.In conclusion, taking switching rates as surrogate markers of treatment failure, this real-life study-the largest in the field-shows that in a more patient-oriented (as in Chinese medical culture), and less symptom-oriented (as in Western medical attitudes), Dapoxetine is a successful treatment for PE patients, with higher reliability when used alone or as part of combined and integrated therapies

Utility of clinical metagenomics in diagnosing malignancies in a cohort of patients with Epstein-Barr virus positivity

BackgroundsDifferentiation between benign and malignant diseases in EBV-positive patients poses a significant challenge due to the lack of efficient diagnostic tools. Metagenomic Next-Generation Sequencing (mNGS) is commonly used to identify pathogens of patients with fevers of unknown-origin (FUO). Recent studies have extended the application of Next-Generation Sequencing (NGS) in identifying tumors in body fluids and cerebrospinal fluids. In light of these, we conducted this study to develop and apply metagenomic methods to validate their role in identifying EBV-associated malignant disease.MethodsWe enrolled 29 patients with positive EBV results in the cohort of FUO in the Department of Infectious Diseases of Huashan Hospital affiliated with Fudan University from 2018 to 2019. Upon enrollment, these patients were grouped for benign diseases, CAEBV, and malignant diseases according to their final diagnosis, and CNV analysis was retrospectively performed in 2022 using samples from 2018 to 2019.ResultsAmong the 29 patients. 16 of them were diagnosed with benign diseases, 3 patients were diagnosed with CAEBV and 10 patients were with malignant diseases. 29 blood samples from 29 patients were tested for mNGS. Among all 10 patients with malignant diagnosis, CNV analysis suggested neoplasms in 9 patients. Of all 19 patients with benign or CAEBV diagnosis, 2 patients showed abnormal CNV results. The sensitivity and specificity of CNV analysis for the identification for tumors were 90% and 89.5%, separately.ConclusionsThe application of mNGS could assist in the identification of microbial infection and malignancies in EBV-related diseases. Our results demonstrate that CNV detection through mNGS is faster compared to conventional oncology tests. Moreover, the convenient collection of peripheral blood samples adds to the advantages of this approach

COVID Pandemic Impact on Healthcare Provision and Patient Psychosocial Distress: A Multi-National Cross-Sectional Survey among Asia-Pacific Countries

Abstract Purpose COVID pandemic significantly affected the delivery and maintenance of healthcare system, resulting in greater utilization of digital health interventions. Materials and Methods This multi-national cross-sectional survey was administered to clinicians working in major Asia-Pacific cities during the mandatory social lockdown period in June 2020. Clinical demographics and professional data, delivery of Andrology-related healthcare services, and patient distress based on validated questionnaires such as Depression and Anxiety Stress Scales (DASS) and Decisional Engagement Scale (DES) were collected. Results Telehealth medicine was instituted in all the centres with the majority of centres (92.9%) reported a 50% or more reduction in out-patient related services. The numbers of phone calls, emails correspondence and educational webinars have significantly increased. Despite the provision of reasons for changes in healthcare service and delay in surgery, more than half of the patients (57.1%) rated 2 on the DASS score for the item on patients over-react to situations, while a third of the patients (35.7%) scored a 2 for DASS item on patients being more demanding or unreasonable. The DES scores were more positive with most patients reported a score above 7 out of 10 in terms of items on accepting current arrangement (85.7%), confident in clinician decision-making about treatment (92.9%) and comfortable that the decision is consistent with their preferences (71.4%). Most patients (85.7%) indicated their preferences for more detailed information on healthcare provision. Conclusions Our study showed telehealth services were integrated early and successfully during the COVID pandemic and patients were generally receptive with minimal psychosocial distress

Realization of N-Type Semiconducting of Phosphorene through Surface Metal Doping and Work Function Study

Phosphorene becomes an important member of the layered nanomaterials since its discovery for the fabrication of nanodevices. In the experiments, pristine phosphorene shows p-type semiconducting with no exception. To reach its full capability, n-type semiconducting is a necessity. Here, we report the electronic structure engineering of phosphorene by surface metal atom doping. Five metal elements, Cu, Ag, Au, Li, and Na, have been considered which could form stable adsorption on phosphorene. These elements show patterns in their electron configuration with one valence electron in their outermost s-orbital. Among three group 11 elements, Cu can induce n-type degenerate semiconducting, while Ag and Au can only introduce localized impurity states. The distinct ability of Cu, compared to Ag and Au, is mainly attributed to the electronegativity. Cu has smaller electronegativity and thus denotes its electron to phosphorene, upshifting the Fermi level towards conduction band, resulting in n-type semiconducting. Ag and Au have larger electronegativity and hardly transfer electrons to phosphorene. Parallel studies of Li and Na doping support these findings. In addition, Cu doping effectively regulates the work function of phosphorene, which gradually decreases upon increasing Cu concentration. It is also interesting that Au can hardly change the work function of phosphorene

Unsupervised Learning of 3D Semantic Keypoints with Mutual Reconstruction

CVLA

DTCC: Multi-level dilated convolution with transformer for weakly-supervised crowd counting

Abstract Crowd counting provides an important foundation for public security and urban management. Due to the existence of small targets and large density variations in crowd images, crowd counting is a challenging task. Mainstream methods usually apply convolution neural networks (CNNs) to regress a density map, which requires annotations of individual persons and counts. Weakly-supervised methods can avoid detailed labeling and only require counts as annotations of images, but existing methods fail to achieve satisfactory performance because a global perspective field and multi-level information are usually ignored. We propose a weakly-supervised method, DTCC, which effectively combines multi-level dilated convolution and transformer methods to realize end-to-end crowd counting. Its main components include a recursive swin transformer and a multi-level dilated convolution regression head. The recursive swin transformer combines a pyramid visual transformer with a fine-tuned recursive pyramid structure to capture deep multi-level crowd features, including global features. The multi-level dilated convolution regression head includes multi-level dilated convolution and a linear regression head for the feature extraction module. This module can capture both low- and high-level features simultaneously to enhance the receptive field. In addition, two regression head fusion mechanisms realize dynamic and mean fusion counting. Experiments on four well-known benchmark crowd counting datasets (UCF_CC_50, ShanghaiTech, UCF_QNRF, and JHU-Crowd++) show that DTCC achieves results superior to other weakly-supervised methods and comparable to fully-supervised methods

MIMO Integrated Sensing and Communication with Extended Target: CRB-Rate Tradeoff

This paper studies a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system, in which a multi-antenna base station (BS) sends unified wireless signals to estimate an extended target and communicate with a multi-antenna communication user (CU) at the same time. We investigate the fundamental tradeoff between the estimation Cram\'er-Rao bound (CRB) for sensing and the data rate for communication, by characterizing the Pareto boundary of the achievable CRB-rate (C-R) region. Towards this end, we formulate a new MIMO rate maximization problem by optimizing the transmit covariance matrix at the BS, subject to a new form of maximum CRB constraint together with a maximum transmit power constraint. We derive the optimal transmit covariance solution in a semi-closed form, by first implementing the singular-value decomposition (SVD) to diagonalize the communication channel and then properly allocating the transmit power over these subchannels for communication and other orthogonal subchannels (if any) for dedicated sensing. It is shown that the optimal transmit covariance is of full rank, which unifies the conventional rate maximization design with water-filling power allocation and the CRB minimization design with isotropic transmission. Numerical results are provided to validate the performance achieved by our proposed optimal design, in comparison with other benchmark schemes