The computer vision precision. Limit precision of edge localisation

The key question of computer vision inspection is the edge localization precision in digital images. The method of image primitive localization with subpixel precision is essentially the interpolation in the significant zones . The sensitivity of an image acquisition system is limited by the quantification error, even an input signal is correctly sampled according ta Shannon theorem, there are certain input changes that we could not detect . This makes a « black zone» and il is difficult to prove a measure precision higher than the dimension of the « black zone » .This paper analyses the limite precision of edge localization and dimensional measure in digital grey images according to dynamic luminance digitization interval and the system impulse response function with the help of « black zone » . The noise influence on « black zone » is also studied.Le problème clé de l'inspection assistée par la vision artificielle est la précision de localisation des contours dans l'image numérique délivrée par le système d'acquisition . La méthode permettant d'atteindre une précision supérieure à la dimension inter-pixel est l'interpolation des zones d'intérêt . Même si les hypothèses du théorème de Shannon sont respectées, la détection du déplacement d'un contour et/ou une mesure dimensionnelle précise peuvent ne pas être possibles sur les échantillons disponibles à cause de la quantification de luminance . Celle-ci crée une « zone noire » (ZN) et il est alors difficile de justifier des précisions de mesure qui seraient inférieures à la dimension de cette ZN .Cet article analyse la limite de précision pour la localisation d'un contour et pour les mesures dimensionnelles sur des images en niveaux de gris en fonction de l'intervalle dynamique de numérisation de luminance et de la réponse impulsionnelle du système à l'aide du concept de la zone noire, ZN. L'influence du bruit sur la ZN est également étudiée

An integrated control and protection scheme based on FBSM-MMC active current limiting strategy for DC distribution network

DC faults can easily lead to overcurrent in DC distribution networks; these faults pose serious threats to the safe operation of the system. The blocking of modular multilevel converters based on the full-bridge sub-modules (FBSM-MMC) is mostly utilized to cut off the fault current. However, the blocking causes short-term blackouts in the entire DC distribution network and there are presently no effective solutions to address this problem. In this study, an integrated control and protection scheme based on the FBSM-MMC active current limiting strategy is proposed. The project includes three stages: first, MMC active current limiting strategy is used to limit the output current of the converter to about 1.2 p.u. after the occurrence of the fault (Stage 1); next, faulty lines are identified based on the asynchronous zero-crossing features of the DC currents of the two ends of the line (Stage 2); then, a fault isolation scheme based on the cooperation of converters, DC circuit breakers, and high-speed switches is proposed to isolate the faulty line (Stage 3). The distribution network can restart quickly via control of the converters. Finally, the simulation of a four-terminal flexible DC distribution network in PSCAD/EMTDC demonstrates the effectiveness of the proposed integrated scheme

Pain-Related Factors and Their Impact on Quality of Life in Chinese Patients With Amyotrophic Lateral Sclerosis

ObjectivesPain is considered a common symptom in amyotrophic lateral sclerosis (ALS). However, the results of studies on pain in ALS are limited and inconsistent. The aim of our study was to comprehensively evaluate the potential factors of pain and effects on quality of life (QoL) in patients with ALS from China.Participants and MethodsPatients were eligible if they fulfilled the criteria of probable and definitive ALS according to the revised El Escorial criteria. Pain was assessed by the Brief Pain Inventory (BPI). Disease severity, sleep quality, fatigue, anxiety, depression, and quality of life (QoL) were evaluated in ALS patients by the ALS Functional Rating Scale-revised (ALSFRS-R) and ALS severity scale (ALSSS), Pittsburgh Sleep Quality Index (PSQI), Fatigue Severity Scale (FSS), Hamilton Anxiety Rating Scale (HARS), Hamilton Depression Rating Scale (HDRS) and McGill Quality of Life Questionnaire (MQOL). Then, the clinical characteristics of ALS patients with pain were compared with those without pain. Last, associated factors of pain, as well as impact on QoL in Chinese ALS patients, were assessed.ResultsA total of 86 ALS patients were included. ALS patients with pain tended to have higher FSS scores and poorer QoL. The FSS score and ALSSS [lower extremity (LE) + upper extremity (UE)] were associated with pain in ALS patients. The ALS Functional Rating Scale-revised (ALSFRS-R), Pain Severity Index (PSI), HARS and HDRS scores were significantly associated with both the physical and psychological domains of QoL.ConclusionOur study was the first to comprehensively evaluate factors associated with pain in Chinese ALS patients, finding that fatigue can be a risk factor for pain and ALSSS (LE + UE) score was related with pain intensity. Additionally, we identified the adverse effects of ALSSS (LE + UE), HARS and HDRS scores on QoL in Chinese ALS patients

Epistasis in neurotransmitter receptors linked to posttraumatic stress disorder and major depressive disorder comorbidity in traumatized Chinese

BackgroundPosttraumatic stress disorder (PTSD) and major depressive disorder (MDD) comorbidity occurs through exposure to trauma with genetic susceptibility. Neuropeptide-Y (NPY) and dopamine are neurotransmitters associated with anxiety and stress-related psychiatry through receptors. We attempted to explore the genetic association between two neurotransmitter receptor systems and the PTSD–MDD comorbidity.MethodsFour groups were identified using latent profile analysis (LPA) to examine the patterns of PTSD and MDD comorbidity among survivors exposed to earthquake-related trauma: low symptoms, predominantly depression, predominantly PTSD, and PTSD–MDD comorbidity. NPY2R (rs4425326), NPY5R (rs11724320), DRD2 (rs1079597), and DRD3 (rs6280) were genotyped from 1,140 Chinese participants exposed to earthquake-related trauma. Main, gene–environment interaction (G × E), and gene–gene interaction (G × G) effects for low symptoms, predominantly depression, and predominantly PTSD were tested using a multinomial logistic model with PTSD–MDD comorbidity as a reference.ResultsThe results demonstrated that compared to PTSD–MDD comorbidity, epistasis (G × G) NPY2R-DRD2 (rs4425326 × rs1079597) affects low symptoms (β = −0.66, OR = 0.52 [95% CI: 0.32–0.84], p = 0.008, pperm = 0.008) and predominantly PTSD (β = −0.56, OR = 0.57 [95% CI: 0.34–0.97], p = 0.037, pperm = 0.039), while NPY2R-DRD3 (rs4425326 × rs6280) impacts low symptoms (β = 0.82, OR = 2.27 [95% CI: 1.26–4.10], p = 0.006, pperm = 0.005) and predominantly depression (β = 1.08, R = 2.95 [95% CI: 1.55–5.62], p = 0.001, pperm = 0.001). The two G × G effects are independent.ConclusionNPY and dopamine receptor genes are related to the genetic etiology of PTSD–MDD comorbidity, whose specific mechanisms can be studied at multiple levels

DeepSeek-VL: Towards Real-World Vision-Language Understanding

We present DeepSeek-VL, an open-source Vision-Language (VL) Model designed for real-world vision and language understanding applications. Our approach is structured around three key dimensions: We strive to ensure our data is diverse, scalable, and extensively covers real-world scenarios including web screenshots, PDFs, OCR, charts, and knowledge-based content, aiming for a comprehensive representation of practical contexts. Further, we create a use case taxonomy from real user scenarios and construct an instruction tuning dataset accordingly. The fine-tuning with this dataset substantially improves the model's user experience in practical applications. Considering efficiency and the demands of most real-world scenarios, DeepSeek-VL incorporates a hybrid vision encoder that efficiently processes high-resolution images (1024 x 1024), while maintaining a relatively low computational overhead. This design choice ensures the model's ability to capture critical semantic and detailed information across various visual tasks. We posit that a proficient Vision-Language Model should, foremost, possess strong language abilities. To ensure the preservation of LLM capabilities during pretraining, we investigate an effective VL pretraining strategy by integrating LLM training from the beginning and carefully managing the competitive dynamics observed between vision and language modalities. The DeepSeek-VL family (both 1.3B and 7B models) showcases superior user experiences as a vision-language chatbot in real-world applications, achieving state-of-the-art or competitive performance across a wide range of visual-language benchmarks at the same model size while maintaining robust performance on language-centric benchmarks. We have made both 1.3B and 7B models publicly accessible to foster innovations based on this foundation model.Comment: https://github.com/deepseek-ai/DeepSeek-V

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

In the era of large language models, Mixture-of-Experts (MoE) is a promising architecture for managing computational costs when scaling up model parameters. However, conventional MoE architectures like GShard, which activate the top-$K$ out of $N$ experts, face challenges in ensuring expert specialization, i.e. each expert acquires non-overlapping and focused knowledge. In response, we propose the DeepSeekMoE architecture towards ultimate expert specialization. It involves two principal strategies: (1) finely segmenting the experts into $mN$ ones and activating $mK$ from them, allowing for a more flexible combination of activated experts; (2) isolating $K_s$ experts as shared ones, aiming at capturing common knowledge and mitigating redundancy in routed experts. Starting from a modest scale with 2B parameters, we demonstrate that DeepSeekMoE 2B achieves comparable performance with GShard 2.9B, which has 1.5 times the expert parameters and computation. In addition, DeepSeekMoE 2B nearly approaches the performance of its dense counterpart with the same number of total parameters, which set the upper bound of MoE models. Subsequently, we scale up DeepSeekMoE to 16B parameters and show that it achieves comparable performance with LLaMA2 7B, with only about 40% of computations. Further, our preliminary efforts to scale up DeepSeekMoE to 145B parameters consistently validate its substantial advantages over the GShard architecture, and show its performance comparable with DeepSeek 67B, using only 28.5% (maybe even 18.2%) of computations

The apicoplast link to fever-survival and artemisinin-resistance in the malaria parasite.

The emergence and spread of Plasmodium falciparum parasites resistant to front-line antimalarial artemisinin-combination therapies (ACT) threatens to erase the considerable gains against the disease of the last decade. Here, we develop a large-scale phenotypic screening pipeline and use it to carry out a large-scale forward-genetic phenotype screen in P. falciparum to identify genes allowing parasites to survive febrile temperatures. Screening identifies more than 200 P. falciparum mutants with differential responses to increased temperature. These mutants are more likely to be sensitive to artemisinin derivatives as well as to heightened oxidative stress. Major processes critical for P. falciparum tolerance to febrile temperatures and artemisinin include highly essential, conserved pathways associated with protein-folding, heat shock and proteasome-mediated degradation, and unexpectedly, isoprenoid biosynthesis, which originated from the ancestral genome of the parasite's algal endosymbiont-derived plastid, the apicoplast. Apicoplast-targeted genes in general are upregulated in response to heat shock, as are other Plasmodium genes with orthologs in plant and algal genomes. Plasmodium falciparum parasites appear to exploit their innate febrile-response mechanisms to mediate resistance to artemisinin. Both responses depend on endosymbiont-derived genes in the parasite's genome, suggesting a link to the evolutionary origins of Plasmodium parasites in free-living ancestors