Additive Margin Softmax for Face Verification Wang, Feng; Cheng, Jian; Liu, Weiyang ...
IEEE signal processing letters,
2018-July, 2018-7-00, Letnik:
25, Številka:
7
Journal Article
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In this letter, we propose a conceptually simple and intuitive learning objective function, i.e., additive margin softmax, for face verification. In general, face verification tasks can be viewed as ...metric learning problems, even though lots of face verification models are trained in classification schemes. It is possible when a large-margin strategy is introduced into the classification model to encourage intraclass variance minimization. As one alternative, angular softmax has been proposed to incorporate the margin. In this letter, we introduce another kind of margin to the softmax loss function, which is more intuitive and interpretable. Experiments on LFW and MegaFace show that our algorithm performs better when the evaluation criteria are designed for very low false alarm rate.
This paper presents an in-depth study and analysis of the model of higher education using distributed hardware tracking intervention of information technology. The MEC-based dynamic adaptive video ...stream caching technology model is proposed. The model dynamically adjusts the bit rate by referring to the broadband estimation and cache occupancy data to ensure users have a smooth experience effect. Simulation results show that the model has fewer transcoding times and generates lower latency than the traditional model, which is suitable for dual-teacher classroom scenarios and further improves the quality of the user’s video viewing experience. The model uses an edge cloud collaborative architecture to migrate the rendering technology to an edge server closer to the user side, enabling real-time interaction, computation, and rendering, reducing the time of data transmission as well as computation time. According to the blended learning-based adaptive intervention model, three rounds of teaching practice are conducted to validate the effectiveness of the intervention model in terms of both student process performance and outcome performance, thereby improving learning adaptability and improving learning effect. Teachers’ teaching has a significant impact on learning motivation (β=0.311, p<0.01), which in turn affects learning adaptability. Teachers use scientific teaching methods to stimulate students’ learning motivation, mobilize enthusiasm, and improve learning adaptability. Under the communication topology of the system as a directed graph, a multi-intelligent system dynamic model with grouping is established; i.e., the intragroup intelligence has the same dynamics but is different between groups, and all system dynamics are unknown. The proposed novel policy iterative algorithm is used to learn the optimal control protocol and achieve optimal consistency control. The effectiveness of the algorithm is demonstrated by the simulation experimental results. The simulation results show that the model has lower latency and energy consumption compared to the cloud rendering model, which is suitable for the safety education classroom scenario and solves the outstanding problems of network connection rate and cloud service latency.
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DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Traditional treatments such as chemotherapy and surgery usually cause severe side effects and excruciating pain. The emergence of nanomedicines and minimally invasive therapies (MITs) has brought ...hope to patients with malignant diseases. Especially, minimally invasive nanomedicines (MINs), which combine the advantages of nanomedicines and MITs, can effectively target pathological cells/tissues/organs to improve the bioavailability of drugs, minimize side effects and achieve painless treatment with a small incision or no incision, thereby acquiring good therapeutic effects. In this review, we provide a comprehensive review of the research status and challenges of MINs, which generally refers to the medical applications of nanotechnology in photo-/ultrasound-/radiation-/magnetism-mediated therapy and imaging. Additionally, we also discuss their combined application in various fields including cancers, cardiovascular diseases, tissue engineering, neuro-functional diseases, and infectious diseases. The prospects, and potential bench-to-bedside translation of MINs are also presented in this review. We expect that this review can inspire the broad interest for a wide range of readers working in the fields of interdisciplinary subjects including (but not limited to) chemistry, nanomedicine, bioengineering, nanotechnology, materials science, pharmacology, and biomedicine.
This review systematically summarizes the research status, challenges, prospects, and potential bench-to-bedside translation of minimally invasive nanomedicines.
Genome-wide association study (GWAS) has become a widely accepted strategy for decoding genotype-phenotype associations in many species thanks to advances in next-generation sequencing (NGS) ...technologies. Maize is an ideal crop for GWAS and significant progress has been made in the last decade. This review summarizes current GWAS efforts in maize functional genomics research and discusses future prospects in the omics era. The general goal of GWAS is to link genotypic variations to corresponding differences in phenotype using the most appropriate statistical model in a given population. The current review also presents perspectives for optimizing GWAS design and analysis. GWAS analysis of data from RNA, protein, and metabolite-based omics studies is discussed, along with new models and new population designs that will identify causes of phenotypic variation that have been hidden to date. The joint and continuous efforts of the whole community will enhance our understanding of maize quantitative traits and boost crop molecular breeding designs.
This review summarizes recent progress in maize GWAS to establish new insights of functional genomics in the omics era. Particularly, potential contributions from over-genomic variants, innovations for statistical methods, and distinctive population designs are highlighted to jointly address the missing heritability issue.
Existing person re-identification has achieved great progress in the visible domain, capturing all the person images with visible cameras. However, in a 24-hour intelligent surveillance system, the ...visible cameras may be noneffective at night. In this situation, thermal cameras are the best supplemental components, which capture images without depending on visible light. Therefore, in this paper, we investigate the visible-thermal cross-modality person re-identification (VT Re-ID) problem. In VT Re-ID, there are two knotty problems should be well handled, cross-modality discrepancy and intra-modality variations. To address these two issues, we propose focusing on enhancing the discriminative feature learning (EDFL) with two extremely simple means from two core aspects, (1) skip-connection for mid-level features incorporation to improve the person features with more discriminability and robustness, and (2) dual-modality triplet loss to guide the training procedures by simultaneously considering the cross-modality discrepancy and intra-modality variations. Additionally, the two-stream CNN structure is adopted to learn the multi-modality sharable person features. The experimental results on two datasets show that our proposed EDFL approach distinctly outperforms state-of-the-art methods by large margins, demonstrating the effectiveness of our EDFL to enhance the discriminative feature learning for VT Re-ID.
The great success achieved by the two highly-effective messenger RNA (mRNA) vaccines during the COVID-19 pandemic highlights the great potential of mRNA technology. Through the evolution of mRNA ...technology, chemistry has played an important role from mRNA modification to the synthesis of mRNA delivery platforms, which allows various applications of mRNA to be achieved both
in vitro
and
in vivo
. In this tutorial review, we provide a summary and discussion on the significant progress of emerging mRNA technologies, as well as the underlying chemical designs and principles. Various nanoparticle (NP)-based delivery strategies including protein-mRNA complex, lipid-based carriers, polymer-based carriers, and hybrid carriers for the efficient delivery of mRNA molecules are presented. Furthermore, typical mRNA delivery platforms for various biomedical applications (
e.g.
, functional protein expression, vaccines, cancer immunotherapy, and genome editing) are highlighted. Finally, our insights into the challenges and future development towards clinical translation of these mRNA technologies are provided.
This review highlights significant progress in mRNA delivery platforms and therapeutic applications from the view of chemistry. Insights into the challenges and future development towards clinical translation of mRNA therapeutics are also provided.
Dear Editor, Flowering adaptability of cultivars to growth condi- tions should be one of the most important targets in crop domestication and selection. We report here the position- al cloning of a ...major pleiotropic QTL, Ghd7.1, which encodes a PSEUDO-RESPONSE REGULATOR 7-like protein. Under long-day conditions, Ghd7.1 greatly de- lays rice heading and enhances grain productivity.
Acoustic sensors play an important role in many areas, such as homeland security, navigation, communication, health care and industry. However, the fundamental pressure detection limit hinders the ...performance of current acoustic sensing technologies. Here, through analytical, numerical and experimental studies, we show that anisotropic acoustic metamaterials can be designed to have strong wave compression effect that renders direct amplification of pressure fields in metamaterials. This enables a sensing mechanism that can help overcome the detection limit of conventional acoustic sensing systems. We further demonstrate a metamaterial-enhanced acoustic sensing system that achieves more than 20 dB signal-to-noise enhancement (over an order of magnitude enhancement in detection limit). With this system, weak acoustic pulse signals overwhelmed by the noise are successfully recovered. This work opens up new vistas for the development of metamaterial-based acoustic sensors with improved performance and functionalities that are highly desirable for many applications.
Photosynthetic pigment-protein complexes (PPCs) accomplish light-energy capture and photochemistry in natural photosynthesis. In this review, we examine three pigment protein complexes in oxygenic ...photosynthesis: light-harvesting antenna complexes and two reaction centers: Photosystem II (PSII), and Photosystem I (PSI). Recent technological developments promise unprecedented insights into how these multi–component protein complexes are assembled into higher order structures and thereby execute their function. Furthermore, the interfacial domain between light-harvesting antenna complexes and PSII, especially the potential roles of the structural loops from CP29 and the PB–loop of ApcE in higher plant and cyanobacteria, respectively, are discussed. It is emphasized that the structural nuances are required for the structural dynamics and consequently for functional regulation in response to an ever–changing and challenging environment.
•Structural similarities of higher plant LHC-PSII assembly and Cyanobacterial PBS-PSII assembly•The structural loop of higher plant CP29 and cyanobacterial PB-loop play similar functional roles mediating complex assembly•The PsbW-PsbI-CP43-D1-PsbO axis acts as a hub sensing proton status
Some metallic tailings from closed mines were scattered in upstream of the Miyun Reservoir, Beijing, threatening the ecological environment of rivers due to trace metals. The Liuli River, one of the ...main rivers affected, was investigated as a typical model in this work. In this study, we selected eight sites to assess interactions among the various geochemical factors especially between trace metals and sediment microbiota. Random forest predicted that low concentrations of Cu, Cd, Cr and Ni (lower than 61.8 mg/kg, 3.2 mg/kg, 173.2 mg/kg and 34.1 mg/kg, respectively) were able to enhance community diversity but generally, trace metals contamination impaired microbial diversity. Environmental factor correlation analysis showed that As, pH and available P were the major factors that shifted the distribution of the microbial communities. Metagenome sequencing revealed that Proteobacteria harbored the vast majority of heavy metal resistance genes followed by Actinobacteria and Bacteroidetes. Metal tolerance of Proteobacteria were achieved by exportation of metals by the corresponding transporters, by pumps and ion channels, or by their reduction via redox reactions. In addition, Proteobacteria harbored a greater ability to repair DNA damage via DNA recombination.
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•The microbial mechanisms of adaptation to heavy metals in sediments was investigated.•Low concentrations of Cu, Cd, Cr, Zn, Pb and Ni were able to enhance biodiversity.•As, pH and AP were the main factors shaping microbial community distribution.•Proteobacteria contained many genes related to DNA repair and heavy-metal resistance.
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