EE<i>k</i>NN: <i>k</i>-Nearest Neighbor Classifier with an Evidential Editing Procedure for Training Samples

The k-nearest neighbor (kNN) rule is one of the most popular classification algorithms applied in many fields because it is very simple to understand and easy to design. However, one of the major problems encountered in using the kNN rule is that all of the training samples are considered equally important in the assignment of the class label to the query pattern. In this paper, an evidential editing version of the kNN rule is developed within the framework of belief function theory. The proposal is composed of two procedures. An evidential editing procedure is first proposed to reassign the original training samples with new labels represented by an evidential membership structure, which provides a general representation model regarding the class membership of the training samples. After editing, a classification procedure specifically designed for evidently edited training samples is developed in the belief function framework to handle the more general situation in which the edited training samples are assigned dependent evidential labels. Three synthetic datasets and six real datasets collected from various fields were used to evaluate the performance of the proposed method. The reported results show that the proposal achieves better performance than other considered kNN-based methods, especially for datasets with high imprecision ratios

Compact Belief Rule Base Learning for Classification with Evidential Clustering

The belief rule-based classification system (BRBCS) is a promising technique for addressing different types of uncertainty in complex classification problems, by introducing the belief function theory into the classical fuzzy rule-based classification system. However, in the BRBCS, high numbers of instances and features generally induce a belief rule base (BRB) with large size, which degrades the interpretability of the classification model for big data sets. In this paper, a BRB learning method based on the evidential C-means clustering (ECM) algorithm is proposed to efficiently design a compact belief rule-based classification system (CBRBCS). First, a supervised version of the ECM algorithm is designed by means of weighted product-space clustering to partition the training set with the goals of obtaining both good inter-cluster separability and inner-cluster pureness. Then, a systematic method is developed to construct belief rules based on the obtained credal partitions. Finally, an evidential partition entropy-based optimization procedure is designed to get a compact BRB with a better trade-off between accuracy and interpretability. The key benefit of the proposed CBRBCS is that it can provide a more interpretable classification model on the premise of comparative accuracy. Experiments based on synthetic and real data sets have been conducted to evaluate the classification accuracy and interpretability of the proposal

Gram-Scale Synthesis of Hydrophilic PEI-Coated AgInS₂ Quantum Dots and Its Application in Hydrogen Peroxide/Glucose Detection and Cell Imaging

Assisted with polyethylenimine, 4.0 L of water-soluble AgInS₂ quantum dots (AIS QDs) were successfully synthesized in an electric pressure cooker. As-prepared QDs exhibit yellow emission with a photoluminescence (PL) quantum yield up to 32%. The QDs also show excellent water/buffer stability. The highly luminescent AIS QDs are used to explore their dual-functional behavior: detection of hydrogen peroxide (H₂O₂)/glucose and cell imaging. The amino-functionalized AIS QDs show high sensitivity and specificity for H₂O₂ and glucose with detection limits of 0.42 and 0.90 μM, respectively. A linear correlation was established between PL intensity and concentration of H₂O₂ in the ranges of 0.5–10 μM and 10–300 μM, while the linear ranges were 1–10 μM and 10–1000 μM for detection of glucose. The AIS QDs reveal negligible cytotoxicity on HeLa cells. Furthermore, the luminescence of AIS QDs gives the function of optical imaging

Submergence Tolerance and Germination Dynamics of Roegneria nutans Seeds in Water-Level Fluctuation Zones with Different Water Rhythms in the Three Gorges Reservoir.

The Three Gorges Dam features two water-level fluctuation zones (WLFZs): the preupland drawdown zone (PU-DZ) and the preriparian drawdown zone (PR-DZ). To investigate the vegetation potential of Roegneria nutans in WLFZs, we compared the submergence tolerance and germination dynamics in the natural riparian zone (NRZ), PU-DZ and PR-DZ. We found that the NRZ seeds maintained an 81.3% intactness rate and >91% germination rate. The final seed germination rate and germination dynamics were consistent with those of the controls. Meanwhile, the PU-DZ seeds submerged at 5 m, 10 m, 15 m, and 20 m exhibited intactness rates of 70.5%, 79.95%, 40.75%, and 39.87%, respectively, and >75% germination. Furthermore, the PR-DZ seeds exhibited intactness rates of 22.44%, 61.13%, 81.87%, and 15.36% at 5 m, 10 m, 15 m, and 17 m, respectively, and 80% germination. The germination rates of the intact seeds submerged >10 m were >80%. Finally, the intact seeds germinated quickly in all WLFZs. The high proportion of intact seeds, rapid germination capacity, and high germination rate permit R. nutans seeds to adapt to the complicated water rhythms of the PU-DZ and PR-DZ and indicate the potential for their use in vegetation restoration and recovery. Thus, perennial seeds can be used for vegetation restoration in the WLFZs of large reservoirs and in other regions with water rhythms similar to the Three Gorges Reservoir

Systems Pharmacology-Based Approach to Comparatively Study the Independent and Synergistic Mechanisms of Danhong Injection and Naoxintong Capsule in Ischemic Stroke Treatment

To provide evidence for the better clinical use of traditional Chinese medicine preparations (TCMPs), comparison of the pharmacological mechanisms between TCMPs with similar therapeutic effect is necessary. However, methodology for dealing with this issue is still scarce. Danhong injection (DHI) and Naoxintong capsule (NXT) are representative TCMPs for ischemic stroke (IS) treatment, which are also frequently used in combination. Here they were employed as research objects to demonstrate the feasibility of systems pharmacology approach in elucidation of the independent and combined effect of TCMPs. By incorporating chemical screening, target prediction, and network construction, a feasible systems pharmacology model has been established to systematically uncover the underlying action mechanisms of DHI, NXT, or their pair in IS treatment. Systematic analysis of the created TCMP-Compound-Target-Disease network revealed that DHI and NXT shared common targets such as PTGS2, F2, ADRB1, IL6, ALDH2, and CCL2, which were involved in the vasomotor system regulation, blood-brain barrier disruption, redox imbalance, neurotrophin activity, and brain inflammation. In comparative mechanism study, the merged DHI/NXT-IS PPI network and pathway enrichment analysis indicated that DHI and NXT exerted the therapeutic effects mainly through immune system and VEGF signaling pathways. Meanwhile, they had their own unique pathways, e.g., calcium signaling pathway for DHI and gap junction for NXT. While for their synergistic mechanism, DHI and NXT participated in chemokine signaling pathway, T cell receptor signaling pathway, VEGF signaling pathway, gap junction, and so on. Our study provided an optimized strategy for dissecting the different and combined effect of TCMPs with similar actions

Tuning the Band Gap of Cu₂ZnSn(S,Se)₄ Thin Films via Lithium Alloying

Alkali metal doping plays a crucial role in fabricating high-performance Cu­(In,Ga)­(S,Se)₂ and Cu₂ZnSn­(S,Se)₄ (CZTSSe) thin film solar cells. In this study, we report the first experimental observation and characterizations of the alloyed Li_<i>x</i>Cu_2–<i>x</i>ZnSn­(S,Se)₄ thin films. It is found that Cu⁺ ions in Cu₂ZnSn­(S,Se)₄ thin films can be substituted with Li⁺ ions, forming homogeneous Li_<i>x</i>Cu_2–<i>x</i>ZnSn­(S,Se)₄ (0 ≤ <i>x</i> ≤ 0.29) alloyed thin films. Consequently, the band gap, conduction band minimum, and valence band maximum of Li_<i>x</i>Cu_2–<i>x</i>ZnSn­(S,Se)₄ thin films are profoundly affected by Li/Cu ratios. The band alignment at the Li_<i>x</i>Cu_2–<i>x</i>ZnSn­(S,Se)₄/CdS interface can be tuned by changing the Li/Cu ratio. We found that the photovoltaic parameters of the Li_<i>x</i>Cu_2–<i>x</i>ZnSn­(S,Se)₄ solar cell devices are strongly influenced by the Li/Cu ratios. Besides, the lattice constant, carrier concentration, and crystal growth of Li_<i>x</i>Cu_2–<i>x</i>ZnSn­(S,Se)₄ thin films were studied in detail