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Publicly available collections of drug-like molecules have grown to comprise 10s of billions of possibilities in recent history due to advances in chemical synthesis. Traditional methods for identifying ``hit'' molecules from a large collection of potential drug-like candidates have relied on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug to its protein target. A major drawback of the approaches is that they require exceptional computing capabilities to consider for even relatively small collections of molecules. Hyperdimensional Computing (HDC) is a recently proposed learning paradigm that is able to leverage low-precision binary vector arithmetic to build efficient representations of the data that can be obtained without the need for gradient-based optimization approaches that are required in many conventional machine learning and deep learning approaches. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated for a range of application areas. We consider existing HDC approaches for molecular property classification and introduce two novel encoding algorithms that leverage the extended connectivity fingerprint (ECFP) algorithm. We show that HDC-based inference methods are as much as 90 times more efficient than more complex representative machine learning methods and achieve an acceleration of nearly 9 orders of magnitude as compared to inference with molecular docking. We demonstrate multiple approaches for the encoding of molecular data for HDC and examine their relative performance on a range of challenging molecular property prediction and drug-protein binding classification tasks. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools.

By utilizing stochastic computing (SC), the hardware consumption of convolutional neural networks (CNNs) can be decreased significantly. However, long stream length is required to produce acceptable results, which leads to extended computation time. As a result, the inherent random fluctuation error and long latency of processing random bitstreams have made previous SC-CNN implementations inefficient compared with conventional binary designs. To address these issues, in this brief, an efficient convolution architecture based on fast FIR algorithm (FFA) is proposed by employing FFA to reduce the computational complexity. Further, the combination of two-line SC and Sobol sequences is applied to decrease the processing cycles. The functional simulation targeting LeNet-5 with MNIST dataset and RTL synthesis results show that the proposed design yields higher area efficiency than previous SC-based ones and achieves 64%, 11% higher efficiency in area and energy compared to the 5-bit fixed-point design while maintaining comparable accuracy.

Cominuscule flag varieties generalize Grassmannians to other Lie types. Schubert varieties in cominuscule flag varieties are indexed by posets of roots labeled long/short. These labeled posets generalize Young diagrams. We prove that Schubert varieties in potentially different cominuscule flag varieties are isomorphic as varieties if and only if their corresponding labeled posets are isomorphic, generalizing the classification of Grassmannian Schubert varieties using Young diagrams by the last two authors. Our proof is type-independent., Comment: 12 pages, 2 tables, 2 figures

This paper summarized the treatment effect of warm acupuncture combined with scraping therapy in relief of symptoms of diabetic peripheral neuropathy and related nursing measures. A special scraping device was used to wipe smoothly along the meridians such as Liver Channel of Foot Jueyin, Kidney Channel of Foot Shaoyin, Spleen Channel of Foot Taiyang and Stomach Channel of Foot Yangming. The warm acupuncture was carried out on Zusanli, Diji, Sanyinjiao and Yongquan acupoints after scraping therapy. The cold and numbness symptoms of lower extremity and foot were relieved after implementation of warm acupuncture combined with scraping therapy.

Mass spectrometry, commonly used for protein identification, generates a massive number of spectra that need to be matched against a large database. In reality, most of them remain unidentified or mismatched due to unexpected post-translational modifications. Open modification search (OMS) has been proposed as a strategy to improve the identification rate by considering every possible change in spectra, but it expands the search space exponentially. In this work, we propose HyperOMS, which redesigns OMS based on hyperdimensional computing to cope with such challenges. Unlike existing algorithms that represent spectral data with floating point numbers, HyperOMS encodes them with high dimensional binary vectors and performs the efficient OMS in high-dimensional space. With the massive parallelism and simple boolean operations, HyperOMS can be efficiently handled on parallel computing platforms. Experimental results show that HyperOMS on GPU is up to $17\times$ faster and $6.4\times$ more energy efficient than the state-of-the-art GPU-based OMS tool while providing comparable search quality to competing search tools., 6 pages, 7 figures, extension of PACT 2022 paper

The recommendation system has become the primary tool used by many Internet application platforms to solve the problem of information overload, and it faces issues such as data sparsity, cold start, and scalability. At present, most social recommendation algorithms only consider the influence of the trust relationship on the user’s feature vector, which indirectly affects the predicted rating, or consider directly trusting friends as neighbor users, which directly affects the predicted rating, but does not consider the direct influence and indirect combining influences to make rating predictions. Therefore, this paper proposes a collaborative filtering recommendation algorithm (ETBRec), which not only considers the trust difference between users but also proposes the definition of experts and considers the direct impact of expert users on prediction ratings and the trustees’ indirect impact of ratings. Among them, the trust difference is realized through trust metrics, including direct trust metrics and indirect trust metrics; the selection of expert users takes into account the user’s degree of trust and user rating attitude; experimental comparisons with various social recommendation algorithms and related recommendation algorithms on the Ciao and Douban datasets. The experimental results show that the ETBRec algorithm performs better on some evaluation indexes such as mean absolute error (MAE) and root mean squared error (RMSE).

This paper summarized the nursing experience of cupping therapy along meridian in treating one case of stiff neck. The cupping therapy was carried out along meridian and acupoint which reflects the painful area according the syndrome differentiation. Nurses had enhanced the observation on patient reactions during the cupping treatment. The cupping therapy is an easy-to-operate technique and effective to relieve the stiff neck-assoicated symptoms.

We prove that Schubert varieties in potentially different Grassmannians are isomorphic as varieties if and only if their corresponding Young diagrams are identical up to a transposition. We also discuss a generalization of this result to Grassmannian Richardson varieties. In particular, we prove that Richardson varieties in potentially different Grassmannians are isomorphic as varieties if their corresponding skew diagrams are semi-isomorphic as posets, and we conjecture the converse. Here, two posets are said to be semi-isomorphic if there is a bijection between their sets of connected components such that the corresponding components are either isomorphic or opposite., Comment: 10 pages, 13 figures

We consider a conjecture that identifies two types of base point free divisors on $\bar{M}_{0,n}$. The first arises from Gromov-Witten theory of a Grassmannian. The second comes from first Chern classes of vector bundles associated to simple Lie algebras in type A. Here we reduce this conjecture on $\bar{M}_{0,n}$ to the same statement for $n=4$. A reinterpretation leads to a proof of the conjecture on $\bar{M}_{0,n}$ for a large class, and we give sufficient conditions for the non-vanishing of these divisors.

We have proposed and experimentally demonstrated a distributed optical fibre sensor (DOFS) based on the hybrid of phase-sensitive optical time domain reflectometry ( Φ -OTDR) and Raman optical time domain reflectometry (ROTDR), which could reconstruct the acoustic and temperature fields all along the sensing fibre at the same time. The Rayleigh back scattering (RBS), Raman Stokes (RS) and Raman anti-Stokes (RAS) generated by the probe pulse were separated by a WDM filter. Then the RBS was received by a heterodyne balanced photo detector (BPD) for quantitative vibration measurement and the dynamic acoustic field reconstruction, while the RS and RAS components were received directly by avalanche photodiodes (APDs) for temperature demodulation. The experimental results have shown that the proposed hybrid system could measure the temperature profile along a 12km long standard single-mode fibre with a maximal temperature uncertainty of 0.95 °C; and a linearity response of R 2 = 0 . 9986 , along with a periodical knocking event detected simultaneously. Meanwhile, a 100 Hz sinusoidal vibration at 12 km distance along the same fibre could be clearly identified. Distributed knocking vibration and temperature was achieved at the same time with high accuracy.

We prove a conjecture of Buch and Mihalcea in the case of the incidence variety X=Fl(1,n-1;n) and determine the structure of its (T-equivariant) quantum K-theory ring. Our results are an interplay between geometry and combinatorics. The geometric side concerns Gromov-Witten varieties of 3-pointed genus 0 stable maps to X with markings sent to Schubert varieties, while on the combinatorial side are formulas for the (equivariant) quantum K-theory ring of X. We prove that the Gromov-Witten variety is rationally connected when one of the defining Schubert varieties is a divisor and another is a point. This implies that the (equivariant) K-theoretic Gromov-Witten invariants defined by two Schubert classes and a Schubert divisor class can be computed in the ordinary (equivariant) K-theory ring of X. We derive a positive Chevalley formula for the equivariant quantum K-theory ring of X and a positive Littlewood-Richardson rule for the non-equivariant quantum K-theory ring of X. The Littlewood-Richardson rule in turn implies that non-empty Gromov-Witten varieties given by Schubert varieties in general position have arithmetic genus 0., Comment: 29 pages. Comments welcome!

Inorganic selenium (Se) is absorbed and enriched by plants and converted into a stable and nutritionally important organic form, which subsequently when consumed by humans or animals results in increased Se tissue levels. Brassica is one of the most potent Se-enriched plants. The aim of this study was to compare differences in Se enrichment between two predominant Brassica plants namely Brassica rapa Linn L. and Brassica tumida Tsenet Lee L. on Se metabolic parameters. Plants exposed to soil Se levels (0, 0.5, 1, 2.5 or 5 mg/kg) were examined on the activity of glutathione peroxidase (GSH-Px), Se levels and expression of Se metabolism related genes using soil pots. Data showed that activities of GSH-Px in leaf and root of the two Brassica species were significantly increased in the presence of Se at 2.5 mg/kg. Se concentrations of leaf, stem and root in B. tumida Tsenet Lee L. and B. rapa Linn L. rose from 0.31 to 21.84-fold (leaf), 1.15 to 15.16-fold (stem) and 2.11 to 15.26-fold (root) in the pr...

In this paper, deep neural network (DNN) is utilized to improve the belief propagation (BP) detection for massive multiple-input multiple-output (MIMO) systems. A neural network architecture suitable for detection task is firstly introduced by unfolding BP algorithms. DNN MIMO detectors are then proposed based on two modified BP detectors, damped BP and max-sum BP. The correction factors in these algorithms are optimized through deep learning techniques, aiming at improved detection performance. Numerical results are presented to demonstrate the performance of the DNN detectors in comparison with various BP modifications. The neural network is trained once and can be used for multiple online detections. The results show that, compared to other state-of-the-art detectors, the DNN detectors can achieve lower bit error rate (BER) with improved robustness against various antenna configurations and channel conditions at the same level of complexity.

Purple soil samples were treated with technical grade endosulfan at 5 concentration levels(0,5,10,20 and 100 mg/kg),and incubated in glass flask in dark environment for 60 d so as to study the effect of endosulfan and its main metabolites on soil enzyme activities,such as urease,nitrate reductase and polyphenol oxidase.Meanwhile,the mass concentrations of α-,β-endosulfan,endosulfan sulfate and endosulfan diol in the soil were determined.The results showed that both of the degradation processes of α-and β-endosulfan accorded with the first-order reaction kinetic equation,and the half-times were obtained as 32—99d and 69—116 d,respectively.The half-time increased with the amount of endosulfan spiked in the soil.The concentration of endosulfan sulfate increased continuously in the first 20 d,and kept basically stable after incubation for 30 d.While the concentration of endosulfan diol first increased and reached maximum at the 15th day,and then decreased gradually.Compared with CK(without endosulfan),urease activity in the soil spiked with 5 mg/kg of endosulfan at the 5th day increased 20.0%.Besides this,urease activity in the soil spiked with 5—20 mg/kg of endosulfan gradually turned from no significant change to inhibition with time,and the inhibition reached maximum at the 60th day.Urease activity was significantly inhibited and the highest decrease percent reached 94.5% at the 5th day in the soil spiked with 100 mg/kg of endosulfan.Pearson correlation analysis indicated that there was significantly negative correlation between urease activity and the concentration of α-,β-endosulfan,endosulfan sulfate,and endosulfan diol,while that was negatively related to the concentration of endosulfan sulfate at the confidence level of 0.05 based on partial correlation analysis.The partial correlation between urease activity and the concentration of α-,β-endosulfan,and endosulfan diol was not significant.It revealed that endosulfan sulfate was an inhibitor to urease.Nitrate reductase activity in the soil spiked with 5 mg/kg of endosulfan increased significantly at the 5th day,and was inhibited with the increases of endosulfan concentration and incubated time,and the highest decrease percent in the soil spiked with 100 mg/kg of endosulfan reached 89.9% at the 60th day.Pearson correlation analysis indicated that there was significantly negative correlation between nitrate reductase activity and the concentration of α-,β-endosulfan,endosulfan sulfate,and endosulfan diol at the confidence level of 0.01,while that was negatively related to the concentration of endosulfan sulfate at the confidence level of 0.01 based on partial correlation analysis.The partial correlation between nitrate reductase activity and the concentration of α-,β-endosulfan,and endosulfan diol was not significant.It revealed that endosulfan sulfate was an inhibitor to nitrate reductase.Polyphenol oxidase activity in the soil spiked with endosulfan changed greatly with time.In general,polyphenol oxidase activity in the soil spiked with 5 mg/kg of endosulfan was inhibited,and that spiked with 10 mg/kg of endosulfan was similar to that of CK,whereas that was significantly lower than that of CK at the 60th day.Compared with CK,polyphenol oxidase activity in the soil spiked with 20 mg/kg of endosulfan had no significant change at the 5th and 30th day,and significantly increased at the 10th and 15th day,and then reached maximum at the 20th day,which was significantly lower at the 60th day,and that in the soil spiked with 100 mg/kg of endosulfan was much higher before the 60th day,and the increase percent reached maximum(139.9%) at the 15th day,and then decreased continuously,finally reached CK level at the 60th day.Pearson correlation analysis indicated that there was significantly positive correlation between polyphenol oxidase activity and the concentration of α-,β-endosulfan,endosulfan sulfate,and endosulfan diol at the confidence level of 0.01,while the partial correlation between polyphenol oxidase activity and their concentration was not significant.These results indicated that the concentrations of α-,β-endosulfan,endosulfan sulfate,and endosulfan diol have little effect on polyphenol oxidase when they exist alone in the soil.

We conducted three experiments for management of Bemisia tabaci (Gennadius) biotype ‘B’ on tomatoes under greenhouse conditions: (i) vertically placing yellow sticky cards either parallel or perpendicular to tomato rows at a rate of 1 per 3-m row; (ii) releasing Eretmocerus sp. nr. rajasthanicus once at 30 adults/m2 in the high whitefly density greenhouses (> 10 adults/plant), or twice at 15 adults/m2 at a 5-day interval in the low whitefly density greenhouses (< 10 adults/plant); and (iii) using combinations of yellow sticky cards that were placed vertically parallel to tomato rows and parasitoids released once at 30/m2 in high whitefly density greenhouses or twice at 15/m2 at a 5-day interval in low whitefly density greenhouses. Our data show that yellow sticky cards trapped B. tabaci adults and significantly reduced whitefly populations on tomato. The yellow sticky cards that were placed parallel to tomato rows caught significantly more whitefly adults than those placed perpendicular to tomato rows on every sampling date. In the treatment where parasitoids were released once at 30/m2 in high whitefly density greenhouses, the number of live whitefly nymphs were reduced from 4.6/leaf to 2.9/leaf in 40 days as compared with those on untreated plants on which live whitefly nymphs increased from 4.4/leaf to 8.9/leaf. In the treatment where parasitoids were released twice at 15/m2 in low whitefly density greenhouses, the numbers of live nymphs of B. tabaci on tomato leaves were reduced from 2.1/leaf to 1.7/leaf in 20 days as compared with those on untreated plants on which numbers of live nymphs of B. tabaci increased from 2.2/leaf to 4.5/leaf. In the treatment of yellow sticky cards and parasitoid release once at 30/m2 in high whitefly density greenhouses, the numbers of live nymphs of B. tabaci on tomato leaves were reduced from 7.2/leaf to 1.9/leaf, and in the treatment of yellow sticky cards and parasitoid release twice at 15/m2 at a 5-day interval at low whitefly density, the numbers of live nymphs of B. tabaci on tomato leaves were reduced from 2.5/leaf to 0.8/leaf; whereas the numbers of live nymphs of B. tabaci on untreated plants increased from 4.4/leaf to 8.9/leaf. An integrated program for management of B. tabaci on greenhouse vegetables by using yellow sticky cards, parasitoids and biorational insecticides is discussed.

We investigated the influence of different content of Zn2+ (0, 2, 4, 8, 16 mmol·kg1) on plant growth, activities of peroxidase (POD) and superoxide dismutase (SOD), free proline content and Zn accumulation in four varieties of ryegrass (Loliurn pereme L.) by pot culture experiment. The results showed that plant biomass increased at the ranges of 0–2 (Tuoya). 0–4 (Yeying), 0–8 mmol·kg1 (Airuisi and Taide), respectively, and then decreased under excess Zn. The activities of POD, SOD and proline content in shoots decreased firstly, and then increased with the increase of Zn content. The plant biomass, activities of POD and SOD in Taide were evidently higher than in the other three varieties. Root tolerance index (RTI) and Zn transport ratio from root to shoot (S/R) in Taide were excced 1.0. The maximum of Zn content was 583.9 mg/kg (at 16 mmol·kg1) in Taide’s shoot.

In the study, it presents an efficient algorithm based on SURF (Speeded Up Robust Features). The method applies the SURF algorithm in the detection and description for image features, first it applies the SURF feature detector in extracting reference images and matching feature points in the image, respectively, then it uses DAISY algorithm instead of the SURF algorithm to calculate the character description of each feature point vector. In the process of feature points matching, the false matching points are eliminated through RANSAC algorithm. Finally, according to the rest of the match point, it can estimate the space geometric transformation parameters between two images and thus matching process is completed. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3951

In constant-payoff finite population games, when selection is weak and population size is large, the one-third law serves as the condition for a strategy to be advantageous. We generalize the result to the case where payoff matrices are environment-dependent and provide a more general law. In this way we model feedback from the environment and show its impact on the dynamics.

A pot experiment was conducted to examine the activity of antioxidant enzymes, the content of malondialdehyde (MDA), proline and protein, and Cd uptake in different rice cultivars exposed to Cd (0, 1 and 5 mg/kg) in the presence of organic acids and ethylenediamine tetraacetic acid (EDTA). The results showed the increase in activity of dismutase (SOD), contents of proline and protein but a decline in activities of peroxidase (POD) and catalase (CAT), and MDA content for cultivars Xiushui63 and IIyou527. The resistance to Cd was higher in Xiushui63 than that in IIyou527 under the same Cd treatment. Cadmium contents in grain, straw and roots of both cultivars were markedly reduced in the presence of organic acids and EDTA. Grain Cd contents was the highest for plants treated with organic acids, followed by organic acids + 1/2EDTA, and the lowest with EDTA; Cd contents in straw and root were the lowest for plants treated with organic acids, followed by organic acids + 1/2EDTA, and the highest with EDTA treatment when exposed to Cd.

BACKGROUND: Diffuse large B-cell lymphomas (DLBCLs) are phenotypically and genetically heterogeneous. Gene-expression profiling has identified subgroups of DLBCL (activated B-cell-like [ABC], germinal-center B-cell-like [GCB], and unclassified) according to cell of origin that are associated with a differential response to chemotherapy and targeted agents. We sought to extend these findings by identifying genetic subtypes of DLBCL based on shared genomic abnormalities and to uncover therapeutic vulnerabilities based on tumor genetics. METHODS: We studied 574 DLBCL biopsy samples using exome and transcriptome sequencing, array-based DNA copy-number analysis, and targeted amplicon resequencing of 372 genes to identify genes with recurrent aberrations. We developed and implemented an algorithm to discover genetic subtypes based on the co-occurrence of genetic alterations. RESULTS: We identified four prominent genetic subtypes in DLBCL, termed MCD (based on the co-occurrence of MYD88L265P and CD79B mutations), BN2 (based on BCL6 fusions and NOTCH2 mutations), N1 (based on NOTCH1 mutations), and EZB (based on EZH2 mutations and BCL2 translocations). Genetic aberrations in multiple genes distinguished each genetic subtype from other DLBCLs. These subtypes differed phenotypically, as judged by differences in gene-expression signatures and responses to immunochemotherapy, with favorable survival in the BN2 and EZB subtypes and inferior outcomes in the MCD and N1 subtypes. Analysis of genetic pathways suggested that MCD and BN2 DLBCLs rely on "chronic active" B-cell receptor signaling that is amenable to therapeutic inhibition. CONCLUSIONS: We uncovered genetic subtypes of DLBCL with distinct genotypic, epigenetic, and clinical characteristics, providing a potential nosology for precision-medicine strategies in DLBCL. (Funded by the Intramural Research Program of the National Institutes of Health and others.).