Anomalous stable hydrogen-oxygen isotope characteristics and water vapor sources of autumn precipitation in the Weihe River basin, Northwest China.

The extreme changes in autumn rain have significant impacts on the ecological environment of Weihe River basin. Based on 117 autumn rain samples and corresponding meteorological data from 2015 to 2021 at Yangling located in the middle of Weihe River basin, we investigated the stable hydrogen and oxygen isotope composition and water vapor sources of precipitation. The results showed that, (1) extreme changes in autumn rainfall in the study area occurred frequently in recent years, which could be divided into extreme-high autumn precipitation year (HAP, 2021), general autumn precipitation year (GAP, 2015-2017, 2019-2020) and extreme-low autumn precipitation year (LAP, 2018) based on the autumn rain index (ARI); (2) the stable isotopes of different types of precipitation differed significantly, with a pattern of LAP>GAP>HAP for both δ2H and δ18O values. the variations of d-excess values and the slopes and intercepts of the meteoric water lines of autumn rain showed opposite trends. The main factor controlling autumn rain anomaly was not the local meteorological parameters, but the El Nino-Southern Oscillation and the Indian Ocean dipole events, which could explain 99% and 93% of the autumn rain isotopic variations, respectively. These coupling phenomena affected water vapor transport intensity of the marine air mass to the northwest inland, which determined autumn rainfall amount and the stable hydrogen-oxygen isotope composition. Our results would be helpful for improving the understanding of autumn rain anomalies in West China, and provide basic data and theoretical support for regional hydrological model building, would thereby better serve water resources management and disaster prevention and reduction.

A Simple Optical Aerosol Sensing Method of Sauter Mean Diameter for Particulate Matter Monitoring.

Mass concentration is a commonly used but insufficient metric to evaluate the particulate matter (PM) exposure hazard. Recent studies have declared that small particles have more serious impacts on human health than big particles given the same mass concentration. However, state-of-the-art PM sensors cannot provide explicit information of the particle size for further analysis. In this work, we adopt Sauter mean diameter (SMD) as a key metric to reflect the particle size besides the mass concentration. To measure SMD, an effective optical sensing method and a proof-of-concept prototype sensor are proposed by using dual wavelengths technology. In the proposed method, a non-linear conversion model is developed to improve the SMD measurement accuracy for aerosol samples of different particle size distributions and reflective indices based on multiple scattering channels. In the experiment of Di-Ethyl-Hexyl-Sebacate (DEHS) aerosols, the outputs of our prototype sensor demonstrated a good agreement with existing laboratory reference instruments with maximum SMD measurement error down to 7.04%. Furthermore, the simplicity, feasibility and low-cost features of this new method present great potential for distributed PM monitoring, to support sophisticated human exposure hazard assessment.

Progressive and Aligned Pose Attention Transfer for Person Image Generation.

This paper proposes a new generative adversarial network for pose transfer, i.e., transferring the pose of a given person to a target pose. We design a progressive generator which comprises a sequence of transfer blocks. Each block performs an intermediate transfer step by modeling the relationship between the condition and the target poses with attention mechanism. Two types of blocks are introduced, namely pose-attentional transfer block (PATB) and aligned pose-attentional transfer block (APATB). Compared with previous works, our model generates more photorealistic person images that retain better appearance consistency and shape consistency compared with input images. We verify the efficacy of the model on the Market-1501 and DeepFashion datasets, using quantitative and qualitative measures. Furthermore, we show that our method can be used for data augmentation for the person re-identification task, alleviating the issue of data insufficiency. Code and pretrained models are available at: https://github.com/tengteng95/Pose-Transfer.git.

Life cycle assessment of underground coal mining in China.

Coal is not only the main fossil fuel in China but also a pollution source. To evaluate the impact of coal production on the environment, a life cycle assessment (LCA) was conducted on the mining process of a typical coal mine in China by using the SimaPro 9.0.0 software. The Ecoinvent v3 database was used to provide the background data, and midpoint results with uncertainty information were calculated using the ReCiPe Midpoint (H) method. After normalising the midpoint results, fossil depletion was identified as the most predominant environmental impact category, followed by marine ecotoxicity, freshwater ecotoxicity, climate change, freshwater eutrophication, and human toxicity. The contribution analysis indicates that coal mining activities, consumption of steel and electricity, and mine ventilation are the key processes causing the above-mentioned environmental impact categories, which should be paid special attention. According to the sensitivity analysis, the primary countermeasures for addressing the environmental issues are to reduce the mining activities and improve the efficiency of coal mining and utilisation. In addition, the quantitative and comparative analyses show that the gas extraction production mode is beneficial to the environment. Finally, technical measures were proposed to promote green and sustainable development of the coal industry. This research can provide guidance for ensuring national energy security and promoting healthy development of the national economy.

Revealing Functional Crosstalk between Distinct Bioprocesses through Reciprocal Functional Tests of Genetically Interacting Genes.

To systematically explore the genes mediating functional crosstalk between metazoan biological processes, we apply comparative genetic interaction (GI) mapping in Saccharomyces cerevisiae and Caenorhabditis elegans to generate an inter-bioprocess network consisting of 178 C. elegans GIs. The GI network spans six annotated biological processes including aging, intracellular transport, microtubule-based processes, cytokinesis, lipid metabolic processes, and anatomical structure development. By proposing a strategy called "reciprocal functional test" for interacting gene pairs, we discover a group of genes that mediate crosstalk between distinct biological processes. In particular, we identify the ribosomal S6 Kinase/RSKS-1, previously characterized as an mTOR (mechanistic target of rapamycin) effector, as a regulator of DAF-2 endosomal recycling transport, which traces a functional correlation between endocytic recycling and aging processes. Together, our results provide an alternative and effective strategy for identifying genes and pathways that mediate crosstalk between bioprocesses with little prior knowledge.

Mechanism of Accelerant on Disperse Dyeing for PET Fiber in the Silicone Solvent Dyeing System.

Disperse dyeing for polyethylene terephthalate (PET) fiber in different non-aqueous solvent dyeing systems have been extensively studied over the past decades. In the present work, disperse dyeing for PET was investigated in a silicone solvent dyeing system. The influence of accelerant on the fiber swelling, uptake of dye, K/S value of dyed fiber, and dye solubility in the silicone solvent were systematically investigated. Compared with no accelerant, the final uptake of the disperse dye (C. I. Disperse Blue 367) could increase to 81% with 20% accelerant in the silicone solvent dyeing system, and the K/S value of dyed fiber was also higher (3.3 for no accelerant vs. 13.2 for accelerant). The influence of accelerant on the performance of disperse dyeing was also studied. Firstly, the solubility of the disperse dye in the silicone solvent can be decreased by the accelerant. Moreover, the solubility of the disperse dye is inversely proportional to the K/S value and the uptake of the dye. In addition, although the silicone solvent can diffuse to the inner fiber and has a partial swelling in the PET fiber, the swelling of PET can be improved by the accelerant. Furthermore, the swelling of fiber can reach equilibrium when the amount of accelerant was 15% (the weight of fiber). Therefore, this eco-friendly dyeing technology has considerable potential for application to a broad array of chemical fibers.

Exact and heuristic algorithms for Space Information Flow.

Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space, such as Euclidean space. The design of algorithms that compute the optimal SIF solutions remains one of the key open problems in SIF. This work proposes the first exact SIF algorithm and a heuristic SIF algorithm that compute min-cost multicast network coding for N (N ≥ 3) given terminal nodes in 2-D Euclidean space. Furthermore, we find that the Butterfly network in Euclidean space is the second example besides the Pentagram network where SIF is strictly better than Euclidean Steiner minimal tree. The exact algorithm design is based on two key techniques: Delaunay triangulation and linear programming. Delaunay triangulation technique helps to find practically good candidate relay nodes, after which a min-cost multicast linear programming model is solved over the terminal nodes and the candidate relay nodes, to compute the optimal multicast network topology, including the optimal relay nodes selected by linear programming from all the candidate relay nodes and the flow rates on the connection links. The heuristic algorithm design is also based on Delaunay triangulation and linear programming techniques. The exact algorithm can achieve the optimal SIF solution with an exponential computational complexity, while the heuristic algorithm can achieve the sub-optimal SIF solution with a polynomial computational complexity. We prove the correctness of the exact SIF algorithm. The simulation results show the effectiveness of the heuristic SIF algorithm.

Cancer cell line specific co-factors modulate the FOXM1 cistrome.

ChIP-seq has been commonly applied to identify genomic occupation of transcription factors (TFs) in a context-specific manner. It is generally assumed that a TF should have similar binding patterns in cells from the same or closely related tissues. Surprisingly, this assumption has not been carefully examined. To this end, we systematically compared the genomic binding of the cell cycle regulator FOXM1 in eight cell lines from seven different human tissues at binding signal, peaks and target genes levels. We found that FOXM1 binding in ER-positive breast cancer cell line MCF-7 are distinct comparing to those in not only other non-breast cell lines, but also MDA-MB-231, ER-negative breast cancer cell line. However, binding sites in MDA-MB-231 and non-breast cell lines were highly consistent. The recruitment of estrogen receptor alpha (ERα) caused the unique FOXM1 binding patterns in MCF-7. Moreover, the activity of FOXM1 in MCF-7 reflects the regulatory functions of ERα, while in MDA-MB-231 and non-breast cell lines, FOXM1 activities regulate cell proliferation. Our results suggest that tissue similarity, in some specific contexts, does not hold precedence over TF-cofactors interactions in determining transcriptional states and that the genomic binding of a TF can be dramatically affected by a particular co-factor under certain conditions.

Connectivity Restoration in Wireless Sensor Networks via Space Network Coding.

The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.

Contextual Refinement of Regulatory Targets Reveals Effects on Breast Cancer Prognosis of the Regulome.

Gene expression regulators, such as transcription factors (TFs) and microRNAs (miRNAs), have varying regulatory targets based on the tissue and physiological state (context) within which they are expressed. While the emergence of regulator-characterizing experiments has inferred the target genes of many regulators across many contexts, methods for transferring regulator target genes across contexts are lacking. Further, regulator target gene lists frequently are not curated or have permissive inclusion criteria, impairing their use. Here, we present a method called iterative Contextual Transcriptional Activity Inference of Regulators (icTAIR) to resolve these issues. icTAIR takes a regulator's previously-identified target gene list and combines it with gene expression data from a context, quantifying that regulator's activity for that context. It then calculates the correlation between each listed target gene's expression and the quantitative score of regulatory activity, removes the uncorrelated genes from the list, and iterates the process until it derives a stable list of refined target genes. To validate and demonstrate icTAIR's power, we use it to refine the MSigDB c3 database of TF, miRNA and unclassified motif target gene lists for breast cancer. We then use its output for survival analysis with clinicopathological multivariable adjustment in 7 independent breast cancer datasets covering 3,430 patients. We uncover many novel prognostic regulators that were obscured prior to refinement, in particular NFY, and offer a detailed look at the composition and relationships among the breast cancer prognostic regulome. We anticipate icTAIR will be of general use in contextually refining regulator target genes for discoveries across many contexts. The icTAIR algorithm can be downloaded from https://github.com/icTAIR.

Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer.

Homologous recombination (HR) is the primary pathway for repairing double-strand DNA breaks implicating in the development of cancer. RNAi-based knockdowns of BRCA1 and RAD51 in this pathway have been performed to investigate the resulting transcriptomic profiles. Here we propose a computational framework to utilize these profiles to calculate a score, named RNA-Interference derived Proliferation Score (RIPS), which reflects cell proliferation ability in individual breast tumors. RIPS is predictive of breast cancer classes, prognosis, genome instability, and neoadjuvant chemosensitivity. This framework directly translates the readout of knockdown experiments into potential clinical applications and generates a robust biomarker in breast cancer.

Context-Sensitive Spelling Correction of Consumer-Generated Content on Health Care.

BACKGROUND: Consumer-generated content, such as postings on social media websites, can serve as an ideal source of information for studying health care from a consumer's perspective. However, consumer-generated content on health care topics often contains spelling errors, which, if not corrected, will be obstacles for downstream computer-based text analysis. OBJECTIVE: In this study, we proposed a framework with a spelling correction system designed for consumer-generated content and a novel ontology-based evaluation system which was used to efficiently assess the correction quality. Additionally, we emphasized the importance of context sensitivity in the correction process, and demonstrated why correction methods designed for electronic medical records (EMRs) failed to perform well with consumer-generated content. METHODS: First, we developed our spelling correction system based on Google Spell Checker. The system processed postings acquired from MedHelp, a biomedical bulletin board system (BBS), and saved misspelled words (eg, sertaline) and corresponding corrected words (eg, sertraline) into two separate sets. Second, to reduce the number of words needing manual examination in the evaluation process, we respectively matched the words in the two sets with terms in two biomedical ontologies: RxNorm and Systematized Nomenclature of Medicine -- Clinical Terms (SNOMED CT). The ratio of words which could be matched and appropriately corrected was used to evaluate the correction system's overall performance. Third, we categorized the misspelled words according to the types of spelling errors. Finally, we calculated the ratio of abbreviations in the postings, which remarkably differed between EMRs and consumer-generated content and could largely influence the overall performance of spelling checkers. RESULTS: An uncorrected word and the corresponding corrected word was called a spelling pair, and the two words in the spelling pair were its members. In our study, there were 271 spelling pairs detected, among which 58 (21.4%) pairs had one or two members matched in the selected ontologies. The ratio of appropriate correction in the 271 overall spelling errors was 85.2% (231/271). The ratio of that in the 58 spelling pairs was 86% (50/58), close to the overall ratio. We also found that linguistic errors took up 31.4% (85/271) of all errors detected, and only 0.98% (210/21,358) of words in the postings were abbreviations, which was much lower than the ratio in the EMRs (33.6%). CONCLUSIONS: We conclude that our system can accurately correct spelling errors in consumer-generated content. Context sensitivity is indispensable in the correction process. Additionally, it can be confirmed that consumer-generated content differs from EMRs in that consumers seldom use abbreviations. Also, the evaluation method, taking advantage of biomedical ontology, can effectively estimate the accuracy of the correction system and reduce manual examination time.

Absolute phase map recovery of two fringe patterns with flexible selection of fringe wavelengths.

A novel approach is proposed to unwrap the phase maps of two fringe patterns in fringe pattern projection-based profilometry. In contrast to existing techniques, where spatial frequencies (i.e., the number of fringes on a pattern) of the two fringe patterns must be integers and coprime, the proposed method is applicable for any two fringe patterns with different fringe wavelengths (i.e., the number of pixels in a fringe) and thus provides more flexibility in the use of fringe patterns. Moreover, compared to the existing techniques, the proposed method is simpler in its implementation and has better antierror capability. Theoretical analysis and experiment results are presented to confirm the effectiveness of the proposed method.

Detection of ADAMTS-4 activity using a fluorogenic peptide-conjugated Au nanoparticle probe in human knee synovial fluid.

A disintegrin and metalloproteinase with thrombospondin motif-4 (ADAMTS-4) plays a pivotal role in degrading aggrecan, which is an early event in cartilage degrading joint diseases such as osteoarthritis (OA). Detection of ADAMTS-4 activity could provide useful clinical information for early diagnosis of such diseases and disease-modifying therapy. Therefore, we developed a ADAMTS-4 detective fluorescent turn-on AuNP probe (ADAMTS-4-D-Au probe) by conjugating gold nanoparticles with a FITC-modified ADAMTS-4-specific peptide (DVQEFRGVTAVIR). When the ADAMTS-4-D-Au probe was incubated with ADAMTS-4, the fluorescence recovered and fluorescence intensity markedly increased in proportion to concentrations of ADAMTS-4 and the probe. A nearly 3-fold increase in fluorescent intensity in response to only 3.9 pM of ADAMTS-4 was detected, whereas almost no fluorescence recovery was observed when the probe was incubated with matrix metalloproteinase (MMP)-1, -3, and -13. These results indicate a relative high sensitivity and specificity of the probe. Moreover, ADAMTS-4-D-Au probe was used to detect ADAMTS-4 activity in synovial fluid from 11 knee surgery patients. A substantial increase in fluorescent intensity was observed in the acute joint injury group as compared to the chronic joint injury and end-stage OA groups, indicating that this simple and low-cost sensing system might serve as a new detection method for ADAMTS-4 activity in biological samples and in screens for inhibitors for ADAMTS-4-related joint diseases. Additionally, this probe could be a potential biomarker for early diagnosis of cartilage-degrading joint diseases.

The Disease and Gene Annotations (DGA): an annotation resource for human disease.

Disease and Gene Annotations database (DGA, http://dga.nubic.northwestern.edu) is a collaborative effort aiming to provide a comprehensive and integrative annotation of the human genes in disease network context by integrating computable controlled vocabulary of the Disease Ontology (DO version 3 revision 2510, which has 8043 inherited, developmental and acquired human diseases), NCBI Gene Reference Into Function (GeneRIF) and molecular interaction network (MIN). DGA integrates these resources together using semantic mappings to build an integrative set of disease-to-gene and gene-to-gene relationships with excellent coverage based on current knowledge. DGA is kept current by periodically reparsing DO, GeneRIF, and MINs. DGA provides a user-friendly and interactive web interface system enabling users to efficiently query, download and visualize the DO tree structure and annotations as a tree, a network graph or a tabular list. To facilitate integrative analysis, DGA provides a web service Application Programming Interface for integration with external analytic tools.

A framework for annotating human genome in disease context.

Identification of gene-disease association is crucial to understanding disease mechanism. A rapid increase in biomedical literatures, led by advances of genome-scale technologies, poses challenge for manually-curated-based annotation databases to characterize gene-disease associations effectively and timely. We propose an automatic method-The Disease Ontology Annotation Framework (DOAF) to provide a comprehensive annotation of the human genome using the computable Disease Ontology (DO), the NCBO Annotator service and NCBI Gene Reference Into Function (GeneRIF). DOAF can keep the resulting knowledgebase current by periodically executing automatic pipeline to re-annotate the human genome using the latest DO and GeneRIF releases at any frequency such as daily or monthly. Further, DOAF provides a computable and programmable environment which enables large-scale and integrative analysis by working with external analytic software or online service platforms. A user-friendly web interface (doa.nubic.northwestern.edu) is implemented to allow users to efficiently query, download, and view disease annotations and the underlying evidences.

Frequency selection in absolute phase maps recovery with two frequency projection fringes.

In a recent published work we proposed a technique to recover the absolute phase maps of two fringe patterns with different spatial frequencies. It is demonstrated that a number of selected frequency pairs can be used for the proposed approach, but the published work did not provide a guideline for frequency selection. In addition, the performance of the proposed technique in terms of its anti-noise capability is not addressed. In this paper, the rules for selecting the two frequencies are presented based on theoretical analysis of the proposed technique. Also, when the two frequencies are given, the anti-noise capability of technique is formulated and evaluated. These theoretical conclusions are verified by experimental results.