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In this paper, we study the following pattern search problem: Given a pair of point sets A and B in fixed dimensional space R^d, with |B| = n, |A| = m and n >= m, the pattern search problem is to find the translations T's of A such that each of the identified translations induces a matching between T(A) and a subset B' of B with cost no more than some given threshold, where the cost is defined as the minimum bipartite matching cost of T(A) and B'. We present a novel algorithm to produce a small set of candidate translations for the pattern search problem. For any B' subseteq B with |B'| = |A|, there exists at least one translation T in the candidate set such that the minimum bipartite matching cost between T(A) and B' is no larger than (1+epsilon) times the minimum bipartite matching cost between A and B' under any translation (i.e., the optimal translational matching cost). We also show that there exists an alternative solution to this problem, which constructs a candidate set of size O(n log^2 n) in O(n log^2 n) time with high probability of success. As a by-product of our construction, we obtain a weak epsilon-net for hypercube ranges, which significantly improves the construction time and the size of the candidate set. Our technique can be applied to a number of applications, including the translational pattern matching problem.

Despite the remarkable progress achieved in the field of non-fullerene acceptor (NFA)-based organic photovoltaics (OPVs) in recent years, the large energy loss remains the major factor limiting the power conversion efficiency (PCE) of in OPVs. Although many studies on polymer OPVs have been reported, low energy loss systems with high efficiency are rarely reported all-small-molecule organic-solar-cells (ASM-OSCs). This is partially because low energetic offset between donors and acceptors is usually required to get small energy loss, which could result in insufficient exciton dissociation driving force, making the trade-off between device performance and energy loss an important research focus. In this article, we reported ASM-OSCs based on three small molecule donors ZR1-C2, ZR1-C3 and ZR1-C4 with small molecule NFAs BTP-C11-N2Cl, BTP-C9-N2F and BTP-C9-N4F. Charge carrier mobilities, exciton dissociation efficiency and charge collection efficiency were measured and calculated for blends ZR1-C3:TP-C11-N4Cl, ZR1-C3:BTP-C9-N2F and ZR1-C3:BTP-C9-N4F, revealing good charge transport property. Morphology characterizations such as AFM, TEM and GIWAXS have been conducted, demonstrating excellent molecular compatibility, suitable phase separation with fibrous structures that provides efficient charge transport channels. By morphology and charge carrier optimization, the highest PCE of 14.29% was achieved with a small nonradiative energy loss of 0.2 eV which, to the best of our knowledge, is the highest PCE value for ASM-OSCs with non-radiative voltage loss ≤ 0.2 eV, reaching a balance between high performance and low energy loss.

Metal-coordination-directed biomolecule crosslinking in nature has been used for synthesizing various biopolymers, including DNA, peptides, proteins, and polysaccharides. However, the RNA biopolymer has been avoided so far, as due to the poor stability of the RNA molecules, the formation of a biopolymer may alter the biological function of the molecules. Herein, for the first time, we report Zn2+ -driven RNA self-assembly forming spherical nanoparticles while retaining the integrity and biological function of RNA. Various functional RNAs of different compositions, shapes, and lengths from 20 to nearly 1000 nucleotides were used, highlighting the versatility of this approach. The assembled nanospheres possess a superior RNA-loading efficiency, pharmacokinetics, and bioavailability. In-vitro and in-vivo evaluation demonstrated mRNA delivery for expressing GFP proteins, and microRNA delivery to triple-negative breast cancer. This coordination-directed self-assembly behavior amplifies the horizons of RNA coordination chemistry and the application scope of RNA-based therapeutics.

On-line process monitoring increases product quality, improves process stability, and lowers costs in manufacturing. This paper presents a study of using time-frequency representation and deep neural networks to enable real-time, intelligent manufacturing process monitoring. Acoustic emission (AE) signals are obtained during machine turning operations, and transformed into a time-frequency (TF) representation (image) format. Deep neural networks are then applied to the images for process classification according to the operation's spindle speed, feed rate, and depth of cut. The signals are nonstationary with frequency content varying in time. Four commonly used time-frequency analysis methods are discussed and compared, such as the short-time Fourier transform (STFT), continuous wavelet transform (CWT), Hilbert-Huang transform (HHT), and Wigner–Ville distribution (WVD). The study finds that the multi-resolution capability of the CWT technique allows it to render more accurate and richer details of the signals. Classification of machine-turning-operation processes through conventional monitoring techniques is challenging. First, there are not theories directly relating the signal characteristics to the physical process. Also, important signal components associated with the physics of the process are masked by heavy noise from the lathe. These lead to difficulties in selecting features to be extracted, and obtaining reliable data of these features. These obstacles are overcome by deep neural networks that are capable of learning and extracting meaningful features in an automatous fashion. A transfer learning approach is adopted in this study by using high-performance, representative deep neural networks previously developed for image classification and recognition, including ShuffleNet, GoogLeNet, ResNet18, ResNet50, VGG16, and DenseNet201. They are applied to the TF images obtained during the machine turning operations for process classification. The VGG16 network yields the highest classification accuracy at 92.67% when applied to processes of 12 classes, which demonstrates the potential and feasibility of the proposed method for satisfactory monitoring performance. Lastly, it is shown that the classification accuracy can be improved by using shallower networks modified from the VGG-16 network to mitigate the overfitting issue. A classification accuracy of 95.58% is achieved by removing two convolutional layers.

Parvalbumin-immunoreactive (Parv+) interneurons is an important component of striatal GABAergic microcircuits, which receive excitatory inputs from the cortex and thalamus, and then target striatal projection neurons. The present study aimed to examine ultrastructural synaptic connection features of Parv+ neruons with cortical and thalamic input, and striatal projection neurons by using immuno-electron microscopy (immuno-EM) and immunofluorescence techniques. Our results showed that both Parv+ somas and dendrites received numerous asymmetric synaptic inputs, and Parv+ terminals formed symmetric synapses with Parv- somas, dendrites and spine bases. Most interestingly, spine bases targeted by Parv+ terminals simultaneously received excitatory inputs at their heads. Electrical stimulation of the motor cortex (M1) induced higher proportion of striatal Parv+ neurons express c-Jun than stimulation of the parafascicular nucleus (PFN), and indicated that cortical- and thalamic-inputs differentially modulate Parv+ neurons. Consistent with that, both Parv + soma and dendrites received more VGlut1+ than VGlut2+ terminals. However, the proportion of VGlut1+ terminal targeting onto Parv+ proximal and distal dendrites was not different, but VGlut2+ terminals tended to target Parv+ somas and proximal dendrites than distal dendrites. These functional and morphological results suggested excitatory cortical and thalamic glutamatergic inputs differently modulate Parv+ interneurons, which provided inhibition inputs onto striatal projection neurons. To maintain the balance between the cortex and thalamus onto Parv+ interneurons may be an important therapeutic target for neurological disorders.

Significant progress has been made in organic solar cells over the past few years. However, the power conversion efficiency of all-small-molecule systems is still lower than that of polymer photovoltaics. Ternary strategies lead to a potential way to improve the performance of all-small-molecule organic solar systems. In this article, an all-small-molecule ternary organic solar cell is presented by incorporating a small amount of the IDIC acceptor into a ZR1-Cl : IDIC-4Cl based binary system. On the basis of the enhanced absorption spectrum, the good miscibility enabled by two structurally similar acceptors can potentially form receptor alloys, leading to a simultaneous increase in both short circuit current density and open circuit voltage to 18.64 mA cm−2 and 0.90 V, respectively. Characterizations such as transmission electron microscopy and grazing-incidence wide-angle scattering confirmed good miscibility, ordered packing and high crystallinity in the ternary film with a fibrous structure that benefits electron transfer, increasing the fill factor to 69.66%. The simultaneous increment in short circuit current, open circuit voltage and fill factor increases the power conversion efficiency from 10.81% in the binary system to 11.65% in the ternary system.

Three small-molecule donors based on dithieno[2,3-d:2ʹ,3ʹ-dʹ]-benzo[1,2-b:4,5-bʹ] dithiophene (DTBDT) unit were designed and synthesized by side chain regulation with chlorinated or/and sulfurated substitutions (namely ZR1, ZR1-Cl, and ZR1-S-Cl respectively), along with a crystalline non-fullerene acceptor IDIC-4Cl with a chlorinated 1,1-dicyanomethylene-3-indanone (IC) end group. Energy levels, molar extinction coefficients and crystallinities of three donor molecules can be effectively altered by combining chlorination and sulfuration strategies. Especially, the ZR1-S-Cl exhibited the best absorption ability, lowest higher occupied molecular orbital (HOMO) energy level and highest crystallinity among three donors, resulting in the corresponding all-small-molecule organic solar cells to produce a high power conversion efficiency (PCE) of 12.05% with IDIC-4Cl as an acceptor.

The energy levels and crystallinity of the polymer donor greatly affect the active layer morphology and device performance in non-fullerene organic solar cells (OSCs). In this work, a new series of polymer donors consisting of dithieno[2,3-d:2′,3′-d′]benzo[1,2-b:4,5-b′]dithiophene (DTBDT) and 2,2′-bithiophene-3,3′-dicarboximide (BTI) units were synthesized and named PDTBDT, PDTBDT-T, and PDTBDT-T-Cl. The BTI unit shows a strong electron withdrawing ability to reduce the highest occupied molecular orbital (HOMO) level and a good planarity to reduce the steric hindrance effectively. The combination of BTI and DTBDT units with high planarity and rigidity magnificently maintains the crystallinity of the polymer, improves that of the acceptor, and obtains a preferred face-on orientation, thereby greatly improving the charge transfer efficiency. The introduced thiophene π-bridges and chlorine atoms in the conjugated structure further optimized light absorption and the energy level of the polymers. With the small molecule Y6 as the acceptor, the optimized OSCs based on PDTBDT-T-Cl:Y6 achieved a power conversion efficiency of 15.63%, which is remarkably higher than those of PDTBDT-T:Y6 (12.71%) and PDTBDT:Y6 (8.22%). These results show that BTI-based polymer donors can achieve comparable performance to the classic polymer donor of PM6 by designing their molecular structure to enhance the crystallinity, promote the stacking of the acceptor, optimize the phase separation morphology, and improve the performance of the device.

For all small-molecule-based organic solar cells (SM-OSCs), it is very challenging to obtain a nanoscale bicontinuous network structure in the active layers, so their power conversion efficiencies (PCEs) still lag behind those of the polymer-based OSCs. In this work, highly efficient SM-OSCs based on a ternary bulk heterojunction (BHJ) layer of B1:BO-2Cl:BO-4Cl were constructed. Ternary cells with the three different BO-2Cl:BO-4Cl weight ratios exhibit higher PCEs than those of B1:BO-2Cl- and B1:BO-4Cl-based binary cells. The results obtained from the transient absorption, time-resolved photoluminescence spectroscopy and device physics analysis reveal that the ternary cell with the optimal composition (B1:BO-2Cl:BO-4Cl = 1 : 0.5 : 0.5 in weight ratio) exhibits faster charge transfer processes, suppressed geminate and non-geminate charge recombination, lower energetic disorder, and higher and more symmetric carrier mobilities than the two binary cells. The transmission electron microscopy measurement results reveal that the nanoscale bicontinuous interpenetrating network with a hierarchical branched structure can be fully evolved in the BHJ layer with the optimal ternary composition. As a result, the optimal ternary cell exhibits a PCE of 17.0% (certified to be 16.9%) and a fill factor of 0.78, which are the highest values obtained for SM-OSCs.

Visual imaging of long noncoding RNA (lncRNA) MEG3, a newfound regulator of transactivation and tumor growth suppression, is conducive to unlock the secrets of MEG3 in some important biological processes. Here, for the first time, we designed a DNA tetrahedron-based three-dimensional (3D) catcher for imaging cytoplasmic lncRNA MEG3 in living cells. The 3D catcher is composed of a triple-helix-forming dsDNA with capacity to bind the 5'-end GA-rich domain of the lncRNA MEG3 and four hairpin-shaped antisense sequences toward contiguous domain on MEG3. Once ingested by the cell, the 3D catcher quickly captures lncRNA MEG3 via forming a DNA-RNA triple-helix structure and triggering the hybridization-based string disassembly of the catcher. Concomitantly, the quenched hairpin is opened and the fluorescent signal undergoes lighting on conversion. Ascribed to the triple-helix-induced "domino effect," the disassembly reaction time is greatly shorter than the reaction with the inability to form a triple helix. The 3D catcher allows detection of long-chain targets as long as 129 nucleotide (129 nt) with a detection limit of 0.36 nM and distinguishes endogenous lncRNA MEG3 fragments in living cells between hepatoma cells and normal hepatocytes, which provides a reliable strategy for monitoring endogenous long fragment nucleic acid biomarkers in early clinical lesion diagnoses.

In this paper, we consider the following sum query problem: Given a point set P in $${\mathbb {R}}^d$$ , and a distance-based function f(p, q) (i.e., a function of the distance between p and q) satisfying some general properties, the goal is to develop a data structure and a query algorithm for efficiently computing a $$(1+\epsilon )$$ -approximate solution to the sum $$\sum _{p \in P} f(p,q)$$ for any query point $$q \in {\mathbb {R}}^d$$ and any small constant $$\epsilon >0$$ . Existing techniques for this problem are mainly based on some core-set techniques which often have difficulties to deal with functions with local domination property. Based on several new insights to this problem, we develop in this paper a novel technique to overcome these encountered difficulties. Our algorithm is capable of answering queries with high success probability in time no more than $${\tilde{O}}_{\epsilon ,d}(n^{0.5 + c})$$ , and the underlying data structure can be constructed in $${\tilde{O}}_{\epsilon ,d}(n^{1+c})$$ time for any $$c>0$$ , where the hidden constant has only polynomial dependence on $$1/\epsilon$$ and d. Our technique is simple and can be easily implemented for practical purpose.

Tiagabine hydrochloride (TGB) is a clinically frequently used drug for anticonvulsion and reducing epileptic frequency. Over administration of TGB could bring about adverse effects, such as speech disorder, depression, and even suicidal tendencies. Therefore, accessible and sensitive assay for analysis of TGB becomes an urgent need toward guiding clinical medication. Here, we present the first report on fluorescence turn-on detection of TGB in urine testing. In this protocol, a fluorescent dye, perylene tetracarboxylic acid imide derivative (PTAI), is found specifically occupying the Sudlow site II of human serum albumin (HSA) and displays a new phenomenon of binding-induced quenching (BIQ). In presence of TGB, competitive binding of the TGB to the site II of HSA will trigger release of PTAI, thus successfully lighting up the fluorescence of PTAI. This label-free assay enjoys a broader working range (1-350 μM) and lower detection limit (0.218 μM) than the traditional liquid chromatography method and is uninterfered by the miscellaneous in the artificial urine. The BIQ probe highlights the merits of HSA as a quencher and a molecular recognition unit, and it opens up a way for studying drug-HSA interaction mechanism and noninvasive pharmaceutical testing.

Astrocytes and astrocyte-related proteins play important roles in maintaining normal brain function, and also regulate pathological processes in brain diseases and injury. However, the role of astrocytes in the dopamine-depleted striatum remains unclear. A rat model of Parkinson’s disease was therefore established by injecting 10 μL 6-hydroxydopamine (2.5 μg/μL) into the right medial forebrain bundle. Immunohistochemical staining was used to detect the immunoreactivity of glial fibrillary acidic protein (GFAP), calcium-binding protein B (S100B), and signal transducer and activator of transcription 3 (STAT3) in the striatum, and to investigate the co-expression of GFAP with S100B and STAT3. Western blot assay was used to measure the protein expression of GFAP, S100B, and STAT3 in the striatum. Results demonstrated that striatal GFAP-immunoreactive cells had an astrocytic appearance under normal conditions, but that dopamine depletion induced a reactive phenotype with obvious morphological changes. The normal striatum also contained S100B and STAT3 expression. S100B-immunoreactive cells were uniform in the striatum, with round bodies and sparse, thin processes. STAT3-immunoreactive cells presented round cell bodies with sparse processes, or were darkly stained with a large cell body. Dopamine deprivation induced by 6-hydroxydopamine significantly enhanced the immunohistochemical positive reaction of S100B and STAT3. Normal striatal astrocytes expressed both S100B and STAT3. Striatal dopamine deprivation increased the number of GFAP/S100B and GFAP/STAT3 double-labeled cells, and increased the protein levels of GFAP, S100B, and STAT3. The present results suggest that morphological changes in astrocytes and changes in expression levels of astrocyte-related proteins are involved in the pathological process of striatal dopamine depletion. The study was approved by Animal Care and Use Committee of Sun Yat-sen University, China (Zhongshan Medical Ethics 2014 No. 23) on September 22, 2014.

This paper presents a thorough evaluation of twenty-one state-of-the-art widely-used crop segmentation algorithms, motived by their significance in vision tasks for further analysis. An ideal crop segmentation algorithm can effectively extract crop information, thus providing an important precondition for the application of intelligent agriculture analytics. In order to enable researchers in this field to fully understand various crop segmentation methods, this paper proposes a new classification strategy of object segmentation by dividing the algorithms into pixel-based and region-based approaches at first, and then systematically evaluating various crop segmentation methods with a unified data benchmark and four common metrics. A new dataset which incorporates crop variety, environment condition and observation distance into consideration is constructed for demonstrating the experiments and comparisons. The effectiveness and robustness of these algorithms were evaluated by three sets of comparative experiments. Based on the quantitative results, we summarize the advantages and disadvantages of the evaluated algorithms from the segmentation performances with four metric indicators. Furthermore, the discussion and evaluation results will provide great support for precision agriculture analysis.

Nano-antibacterial agents can play a critical role in chronic wound management. However, the design of an intelligent nanosystem that can provide both a visual warning of infection and precise sterilization remains a hurdle. Herein, a rod-like porphyrin-based metal-organic framework theranostic nanosystem (Zn-TCPP nanorods) is fabricated via coordination chelation between tetrakis(4-carboxylphenyl)porphyrin and zinc ions. This system can show significant fluorescence activation in response to the local elevated pH shown by chronic wounds, a main indicator of wound infection. Meanwhile, under the guidance of fluorescence imaging, the highly spatiotemporally precise photodynamic inactivation of microorganisms can be carried out without the destruction of surrounding normal cells and nascent cells. The results demonstrated that the Zn-TCPP nanorods were a highly sensitive and reversible probe for sensing alkaline pH levels. Alterations in the fluorescence of the Zn-TCPP nanorods can accurately indicate the infection status and heterogeneity of infection within the wound bed. Under specific light irradiation, the Zn-TCPP nanorods can exterminate 97% of Staphylococcus aureus via the generation of reactive oxygen species (ROS). Assays of extensive wounds demonstrate that the precise fluorescence-imaging-guided suppression of bacterial infection can significantly reduce the mouse mortality rate and accelerate wound healing. This system provides the opportunity for "precision medicine" relating to chronic wounds and some large-area wounds.

Public health safety issues have been plaguing the world since the pandemic outbreak of coronavirus disease (COVID-19). However, most personal protective equipments (PPE) do not have antibacterial and anti- toxicity effects. In this work, we designed and prepared a reusable, antibacterial and anti-toxicity Polyacrylonitrile (PAN) based nanofibrous membrane cooperated with Ag/g-C

Metal-coordination-directed biomolecule crosslinking in nature has been used for synthesizing various biopolymers, including DNA, peptides, proteins, and polysaccharides. However, the RNA biopolymer has been avoided so far, as due to the poor stability of the RNA molecules, the formation of a biopolymer may alter the biological function of the molecules. Herein, for the first time, we report Zn

Truth discovery is a key problem in data analytics which has received a great deal of attention in recent years. In this problem, we seek to obtain trustworthy information from data aggregated from multiple (possibly) unreliable sources. Most of the existing approaches for this problem are of heuristic nature and do not provide any quality guarantee. Very recently, the first quality-guaranteed algorithm has been discovered. However, the running time of the algorithm depends on the spread ratio of the input points and is fully polynomial only when the spread ratio is relatively small. This could restrict the applicability of the algorithm. To resolve this issue, we propose in this paper a new algorithm which yields a $$(1+\epsilon )$$ -approximation in near quadratic time for any dataset with constant probability. Our algorithm relies on a data structure called range cover, which is interesting in its own right. The data structure provides a general approach for solving some high dimensional optimization problems by breaking down them into a small number of parametrized cases.

Dopaminergic neuron degeneration is known to give rise to dendrite injury and spine loss of striatal neurons, however, changes of intrastriatal glutamatergic terminals and their synapses after 6-hydroxydopamine (6OHDA)-induced dopamine (DA)-depletion remains controversial. To confirm the effect of striatal DA-depletion on the morphology and protein levels of corticostriatal and thalamostriatal glutamatergic terminals and synapses, immunohistochemistry, immuno-electron microscope (EM), western blotting techniques were performed on Parkinson's disease rat models in this study. The experimental results of this study showed that: (1) 6OHDA-induced DA-depletion resulted in a remarkable increase of Vesicular glutamate transporter 1 (VGlut1) + and Vesicular glutamate transporter 2 (VGlut2)+ terminal densities at both the light microscope (LM) and EM levels, and VGlut1+ and VGlut2+ terminal sizes were shown to be enlarged by immuno-EM; (2) Striatal DA-depletion resulted in a decrease in both the total and axospinous terminal fractions of VGlut1+ terminals, but the axodendritic terminal fraction was not significantly different from the control group. However, total, axospinous and axodendritic terminal fractions for VGlut2+ terminals declined significantly after striatal DA-depletion. (3) Western blotting data showed that striatal DA-depletion up-regulated the expression levels of the VGlut1 and VGlut2 proteins. These results suggest that 6OHDA-induced DA-depletion affects corticostriatal and thalamostriatal glutamatergic synaptic inputs, which are involved in the pathological process of striatal neuron injury induced by DA-depletion.