116 research outputs found
Non-coherent detection for ultraviolet communications with inter-symbol interference
Ultraviolet communication (UVC) serves as a promising supplement to share the responsibility for the overloads in conventional wireless communication systems. One challenge for UVC lies in inter-symbol-interference (ISI), which combined with the ambient noise, contaminates the received signals and thereby deteriorates the communication accuracy. Existing coherent signal detection schemes (e.g. maximum likelihood sequence detection, MLSD) require channel state information (CSI) to compensate the channel ISI effect, thereby falling into either a long overhead and large computational complexity, or poor CSI acquisition that further hinders the detection performance. Non-coherent schemes for UVC, although capable of reducing the complexity, cannot provide high detection accuracy in the face of ISI. In this work, we propose a novel non-coherent paradigm via the exploration of the UV signal features that are insensitive to the ISI. By optimally weighting and combining the extracted features to minimize the bit error rate (BER), the optimally-weighted non-coherent detection (OWNCD) is proposed, which converts the signal detection with ISI into a binary detection framework with a heuristic decision threshold. As such, the proposed OWNCD avoids the complex CSI estimation and guarantees the detection accuracy. Compared to the state-of-the-art MLSD in the cases of static and time-varying CSI, the proposed OWNCD can gain ∼1 dB and 8 dB in signal-to-noise-ratio (SNR) at the 7% overhead FEC limit (BER of 4.5×10 −3 , respectively, and can also reduce the computational complexity by 4 order of magnitud
SeqVISTA: a graphical tool for sequence feature visualization and comparison
BACKGROUND: Many readers will sympathize with the following story. You are viewing a gene sequence in Entrez, and you want to find whether it contains a particular sequence motif. You reach for the browser's "find in page" button, but those darn spaces every 10 bp get in the way. And what if the motif is on the opposite strand? Subsequently, your favorite sequence analysis software informs you that there is an interesting feature at position 13982–14013. By painstakingly counting the 10 bp blocks, you are able to examine the sequence at this location. But now you want to see what other features have been annotated close by, and this information is buried several screenfuls higher up the web page. RESULTS: SeqVISTA presents a holistic, graphical view of features annotated on nucleotide or protein sequences. This interactive tool highlights the residues in the sequence that correspond to features chosen by the user, and allows easy searching for sequence motifs or extraction of particular subsequences. SeqVISTA is able to display results from diverse sequence analysis tools in an integrated fashion, and aims to provide much-needed unity to the bioinformatics resources scattered around the Internet. Our viewer may be launched on a GenBank record by a single click of a button installed in the web browser. CONCLUSION: SeqVISTA allows insights to be gained by viewing the totality of sequence annotations and predictions, which may be more revealing than the sum of their parts. SeqVISTA runs on any operating system with a Java 1.4 virtual machine. It is freely available to academic users at
Repetitive sequence analysis and karyotyping reveals centromere-associated DNA sequences in radish (Raphanus sativus L.)
Language Models Meet World Models: Embodied Experiences Enhance Language Models
While large language models (LMs) have shown remarkable capabilities across
numerous tasks, they often struggle with simple reasoning and planning in
physical environments, such as understanding object permanence or planning
household activities. The limitation arises from the fact that LMs are trained
only on written text and miss essential embodied knowledge and skills. In this
paper, we propose a new paradigm of enhancing LMs by finetuning them with world
models, to gain diverse embodied knowledge while retaining their general
language capabilities. Our approach deploys an embodied agent in a world model,
particularly a simulator of the physical world (VirtualHome), and acquires a
diverse set of embodied experiences through both goal-oriented planning and
random exploration. These experiences are then used to finetune LMs to teach
diverse abilities of reasoning and acting in the physical world, e.g., planning
and completing goals, object permanence and tracking, etc. Moreover, it is
desirable to preserve the generality of LMs during finetuning, which
facilitates generalizing the embodied knowledge across tasks rather than being
tied to specific simulations. We thus further introduce the classical (EWC) for
selective weight updates, combined with low-rank adapters (LoRA) for training
efficiency. Extensive experiments show our approach substantially improves base
LMs on 18 downstream tasks by 64.28% on average. In particular, the small LMs
(1.3B, 6B, and 13B) enhanced by our approach match or even outperform much
larger LMs (e.g., ChatGPT)
Eavesdropping against bidirectional physical layer secret key generation in fiber communications
Physical layer secret key exploits the random but reciprocal channel features between legitimate users to encrypt their data against fiber-tapping. We propose a novel tapping-based eavesdropper scheme, leveraging its tapped signals from legitimate users to reconstruct their common features and the secret key.EU Horizon 2020: Grant No. 10100828
Soil properties drive a negative correlation between species diversity and genetic diversity in a tropical seasonal rainforest
A negative species-genetic diversity correlation (SGDC) could be predicted by the niche variation hypothesis, whereby an increase in species diversity within community reduces the genetic diversity of the co-occurring species because of the reduction in average niche breadth; alternatively, competition could reduce effective population size and therefore genetic diversity of the species within community. We tested these predictions within a 20 ha tropical forest dynamics plot (FDP) in the Xishuangbanna tropical seasonal rainforest. We established 15 plots within the FDP and investigated the soil properties, tree diversity, and genetic diversity of a common tree species Beilschmiedia roxburghiana within each plot. We observed a significant negative correlation between tree diversity and the genetic diversity of B. roxburghiana within the communities. Using structural equation modeling, we further determined that the inter-plot environmental characteristics (soil pH and phosphorus availability) directly affected tree diversity and that the tree diversity within the community determined the genetic diversity of B. roxburghiana. Increased soil pH and phosphorus availability might promote the coexistence of more tree species within community and reduce genetic diversity of B. roxburghiana for the reduced average niche breadth; alternatively, competition could reduce effective population size and therefore genetic diversity of B. roxburghiana within community
Eavesdropping against bidirectional physical layer secret key generation in fiber communications
Physical layer secret key exploits the random but reciprocal channel features between legitimate users to encrypt their data against fiber-tapping. We propose a novel tapping-based eavesdropper scheme, leveraging its tapped signals from legitimate users to reconstruct their common features and the secret key.EU Horizon 2020: Grant No. 10100828
Mechanistic examination of causes for narrow distribution in an endangered shrub: a comparison of its responses to drought stress with a widespread congeneric species
Although deep rooting is usually considered a drought-tolerant trait, we found that Syringapinnatifolia, a deep rooting and hydrotropic shrub, has a limited distribution in arid areas. To elucidate the mechanisms for its narrow distribution, we conducted two experiments to examine the physiological and morphological responses to water availability and heterogeneity in S. pinnatifolia and a widespread congeneric species, S. oblata. We measured gas exchange, water use efficiency, and plasticity index in plants of these two species grown at different levels of soil water regimes and in containers with patched water distribution. Our results showed that high photosynthetic capacity in the narrowly distributed S. pinnatifolia was an important factor enabling its survival in the harsh sub-alpine environment. High photosynthetic capacity in S. pinnatifolia, however, was obtained at the expense of high transpiratory water loss, resulting in lower integrative water use efficiency. Biomass allocation to roots in S. pinnatifolia increased by 73 % when soil water increased from 75 to 95 % field capacity, suggesting that S. pinnatifolia could be less competitive for above-ground resources under favorable water regimes. The horizontal root hydrotropism and vertical root hydrotropism of S. pinnatifolia in soil with patched water patterns were likely related to compensation for leaf water loss at low soil water level, indicating a limited capacity for homeostasis within the plant for water conservation and lower level of inherent drought-tolerance. In summary, greater degree of morphological plasticity but lower degree of physiological adjustment may be the main causes for the hydrotropism and narrow distribution of S. pinnatifolia in the sub-alpine habitats
Tapping eavesdropper designs against physical layer secret key in point-to-point fiber communications
With the growing demand for service access and data transmission, security issues in optical fiber systems have become increasingly important and the subject of increased research. Physical layer secret key generation (PL-SKG), which leverages the random but common channel properties at legitimate parties, has been shown to be a secure, low-cost, and easily deployed technique as opposed to computational-based cryptography, quantum, and chaos key methods that rely on precise equipment. However, the eavesdropper (Eve) potential for current PL-SKG in fiber communications has been overlooked by most studies to date. Unlike wireless communications, where the randomness comes from the spatial multi-paths that cannot be all captured by Eves, in fiber communications, all the randomness (from transmitted random pilots or channel randomness) is contained in the signals transmitted inside the fiber. This, therefore, enables a tapping Eve to reconstruct the common features of legitimate users from its received signals, and further decrypt the featured-based secret keys. To implement this idea, we designed two Eve schemes against polarization mode distortion (PMD) based PL-SKG and the two-way cross multiplication based PL-SKG. The simulation results show that our proposed Eves can successfully reconstruct the legitimate common feature and the secret key relied upon, leading to secret key rate (SKR) reductions of between three and four orders of magnitude in the PL-SKG schemes studied. As a result, we reveal and demonstrate a novel eavesdropping potential to provide challenges for current physical layer secret key designs. We hope to provide more insightful vision and critical evaluation on the design of new physical layer secret key schemes in optical fiber links, to provide more comprehensively secure, and intelligent optical networks.European Union funding: 101008280 (DIOR) and UK Royal Society Grant: IES\R3\223068
Tapping eavesdropper designs against physical layer secret key in point-to-point fiber communications
With the growing demand for service access and data transmission, security issues in optical fiber systems have become increasingly important and the subject of increased research. Physical layer secret key generation (PL-SKG), which leverages the random but common channel properties at legitimate parties, has been shown to be a secure, low-cost, and easily deployed technique as opposed to computational-based cryptography, quantum, and chaos key methods that rely on precise equipment. However, the eavesdropper (Eve) potential for current PL-SKG in fiber communications has been overlooked by most studies to date. Unlike wireless communications, where the randomness comes from the spatial multi-paths that cannot be all captured by Eves, in fiber communications, all the randomness(from transmitted random pilots or channel randomness) is contained in the signals transmitted inside the fiber. This, therefore, enables a tapping Eve to reconstruct the common features of legitimate users from its received signals, and further decrypt the featured-based secret keys. To implement this idea, we designed two Eve schemes against polarization mode distortion (PMD) based PL-SKG and the two-way cross multiplication based PL-SKG. The simulation results show that our proposed Eves can successfully reconstruct the legitimate common feature and the secret key relied upon, leading to secret key rate (SKR) reductions of between three and four orders of magnitude in the PL-SKG schemes studied. As a result, we reveal and demonstrate a novel eavesdropping potential to provide challenges for current physical layer secret key designs. We hope to provide more insightful vision and critical evaluation on the design of new physical layer secret key schemes in optical fiber links, to provide more comprehensively secure, and intelligent optical network
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