Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive Machine Learning at Scale With CHISSL

We demonstrate CHISSL a scalable client-server system for real-time interactive machine learning. Our system is capable of incorporating user feedback incrementally and immediately without a pre-defined prediction task. Computation is partitioned between a lightweight web-client and a heavyweight server. The server relies on representation learning and off-the-shelf agglomerative clustering to find a dendrogram, which we use to quickly approximate distances in the representation space. The client, using only this dendrogram, incorporates user feedback via transduction. Distances and predictions for each unlabeled instance are updated incrementally and deterministically, with O(n) space and time complexity. Our algorithm is implemented in a functional prototype, designed to be easy to use by non-experts. The prototype organizes the large amounts of data into recommendations. This allows the user to interact with actual instances by dragging and dropping to provide feedback in an intuitive manner. We applied CHISSL to several domains including cyber, social media, and geo-temporal analysis.
Are hedge fund clones attractive financial products for investors?

The subprime crisis, which proved devastating for the hedge fund industry, induced significant losses for investors who ploughed into absolute return funds. In such a context, investigating the opacity surrounding the hedge fund industry and its prohibitive fee structure is of real interest as, within the context of the Madoff scandal, there is strong evidence of a reduction in investor confidence. On the other hand, investors are still looking for attractive returns. Hedge fund clones therefore appear to offer a promising solution as they seek to replicate hedge fund returns at lower fees and with more transparency and liquidity.
Analysis of vibrating lightweight radar antennas

Future military aircraft and UAV's require the installation of lightweight and low-cost Electronically Steerable Antennas (ESA) which are needed by high-performance Airborne Moving Target Indicator and Surface Moving Target Indicator radars. When these antennas are integrated into the skin of air vehicles, they are subject to unsteady aerodynamic loads. Mechanical forces and these aerodynamic loads will cause deformation of the antenna surface. In this paper the effects of vibrations on Direction of Arrival are investigated.
Calcium-permeable AMPA/kainate receptors mediate toxicity and preconditioning by oxygen-glucose deprivation in oligodendrocyte precursors

Hypoxic–ischemic brain injury in premature infants results in cerebral white matter lesions with prominent oligodendroglial injury and loss, a disorder termed periventricular leukomalacia (PVL). We have previously shown that glutamate receptors mediate hypoxic–ischemic injury to oligodendroglial precursor cells (OPCs) in a model of PVL in the developing rodent brain. We used primary OPC cultures to examine the mechanism of cellular toxicity induced by oxygen–glucose deprivation (OGD) to simulate brain ischemia. OPCs were more sensitive to OGD-induced toxicity than mature oligodendrocytes, and OPC toxicity was attenuated by nonselective [2,3-dihydroxy-6-nitro-7-sulfamoylbenzo[f]quinoxaline (NBQX), 6-cyano-7-nitroquinoxaline-2,3-dione], α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-preferring (GYKI 52466), kainate-preferring (γ-d-glutamylaminomethanesulfonic acid), or Ca2+-permeable AMPA/kainate receptor antagonists (joro spider toxin, JSTx) administered either during or after OGD. Furthermore, NBQX or JSTx blocked OGD-induced Ca2+ influx. Relevant to recurrent hypoxic–ischemic insults in developing white matter, we examined the effects of sublethal OGD preconditioning. A prior exposure of OPCs to sublethal OGD resulted in enhanced vulnerability to subsequent excitotoxic or OGD-induced injury associated with an increased Ca2+ influx. AMPA/kainate receptor blockade with NBQX or JSTx either during or after sublethal OGD prevented its priming effect. Furthermore, OGD preconditioning resulted in a down-regulation of the AMPA receptor subunit GluR2 on cell surface that increased Ca2+ permeability of the receptors. Overall, these data suggest that aberrantly enhanced activation of Ca2+-permeable AMPA/kainate receptors may be a major mechanism in acute and repeated hypoxic–ischemic injury to OPCs in disorders of developing cerebral white matter, such as PVL.
Radiative characteristics of aerosol during extreme fire event over Siberia in summer 2012

Abstract. Microphysical and optical properties of aerosol were studied during a mega-fire event in summer 2012 over Siberia using ground-based measurements of spectral solar radiation at the AERONET site in Tomsk and satellite observations. The data were analysed using multi-year (2003–2013) measurements of aerosol characteristics under background conditions and for less intense fires, differing in burning biomass type, stage of fire, remoteness from observation site, etc. ( ordinary smoke). In June–August 2012, the average aerosol optical depth (AOD, 500 nm) had been 0.95 ± 0.86, about a factor of 6 larger than background values (0.16 ± 0.08), and a factor of 2.5 larger than in ordinary smoke. The AOD values were extremely high on 24–28 July and reached 3–5. A comparison with satellite observations showed that ground-based measurements in the region of Tomsk not only reflect the local AOD features, but are also characteristic for the territory of Western Siberia as a whole. Single scattering albedo (SSA, 440 nm) in this period ranged from 0.91 to 0.99 with an average of ∼ 0.96 in the entire wavelength range of 440–1020 nm. The increase in absorptance of aerosol particles (SSA(440 nm) = 0.92) and decrease in SSA with wavelength observed in ordinary smoke agree with the data from multi-year observations in analogous situations in the boreal zone of USA and Canada. Volume aerosol size distribution in extreme and ordinary smoke had a bimodal character with significant prevalence of fine-mode particles, but in summer 2012 the mean median radius and the width of the fine-mode distribution somewhat increased. In contrast to data from multi-year observations, in summer 2012 an increase in the volume concentration and median radius of the coarse mode was observed with growing AOD. The calculations of the average radiative effects of smoke and background aerosol are presented. Compared to background conditions and ordinary smoke, under the extreme smoke conditions the cooling effect of aerosol considerably intensifies: direct radiative effects (DRE) at the bottom (BOA) and at the top of the atmosphere (TOA) are −13, −35, and −60 W m−2 and −5, −14, and −35 W m−2 respectively. The maximal values of DRE were observed on 27 July (AOD(500 nm) = 3.5), when DRE(BOA) reached −150 W m−2, while DRE(TOA) and DRE of the atmosphere were −75 W m−2. During the fire event in summer 2012 the direct radiative effect efficiency varied in range: at the BOA it was −80–−40 W m−2, at the TOA it was −50–−20 W m−2 and in the atmosphere it was −35–−20 W m−2.
Extracellular amino acids and lipid peroxidation products in periventricular white matter during and after cerebral ischemia in preterm fetal sheep

It is widely hypothesized that accumulation of excitatory amino acids, and oxygen free radicals during or after exposure to hypoxia–ischemia play a pivotal role in preterm periventricular white matter injury; however, there is limited evidence in the intact brain. In preterm fetal sheep (0.65 gestation; term 147 days) we found no significant increase in extracellular levels of excitatory amino acids measured by microdialysis in the periventricular white matter during cerebral ischemia induced by bilateral carotid occlusion. There was no significant change in 8‐isoprostane or malondialdehyde levels in the early phase of recovery after occlusion. In contrast, there was a significant delayed increase in most amino acids and in malondialdehyde (but not 8‐isoprostane) that was maximal approximately 2–3 days after occlusion. The increase in glutamate was significantly correlated with a secondary increase in cortical impedance, an index of cytotoxic edema, and with white matter damage 3 days post‐insult. In conclusion, no significant accumulation of cytotoxins was found within immature white matter during cerebral ischemia. Although a minority of fetuses showed a delayed increase in some cytotoxins, this occurred many days after ischemia, in association with secondary cytotoxic edema, strongly suggesting that these changes are mainly a consequence of evolving cell death.
Changes in Capital Structure: Asset Characteristics or Managerial Preferences

We examine leverage changes around mergers by similar-size firms. If asset characteristics drive leverage, both acquirer and target pre-merger leverage should predict long-term post-merger leverage. We find that only acquirer pre-merger leverage has a long-term effect. The effect of target pre-merger leverage, while highly significant right after the merger, disappears after two years. These findings cannot be explained by suboptimal pre-merger leverage of targets, sales of target assets, or corporate governance characteristics. As acquirer managers usually manage the merged firm, our findings support the hypothesis that managerial preferences have a strong effect on firm leverage.
Dual Set Multi-Label Learning

In this paper, we propose a new learning framework named dual set multi-label learning, where there are two sets of labels, and an object has one and only one positive label in each set. Compared to general multi-label learning, the exclusive relationship among labels within the same set, and the pairwise inter-set label relationship are much more explicit and more likely to be fully exploited. To handle such kind of problems, a novel boosting style algorithm with model-reuse and distribution adjusting mechanisms is proposed to make the two label sets help each other. In addition, theoretical analyses are presented to show the superiority of learning from dual label sets to learning directly from all labels. To empirically evaluate the performance of our approach, we conduct experiments on two manually collected real-world datasets along with an adapted dataset. Experimental results validate the effectiveness of our approach for dual set multi-label learning.
The Impact of the Ontarian Minimum Wage on the Unemployment of Women and the Young in Ontario: A Note

The purpose of this research note is to apply to Ontario a methodology developed and applied by one of the authors (Cousineau 1990) to measure the impact of Quebec's minimum wage on the unemployment of women and the young. This is of interest for two reasons. First, it allows us to examine the robustness of the methodology used by Cousineau (1990); and second, it permits us to contribute to the debate now ongoing in Ontario as to the impacts of raising the minimum wage in the province. This is of some interest, given the paucity of information on these impacts. The paper is divided into three parts. In the first one, we briefly summarize the analytical framework used. In the second, we discuss the data and variables used. In the third, we present and analyze regression results for Ontario, compare them to those obtained for Quebec and use them to examine the proposed increase in the minimum wage.
Claudin-4 SPECT Imaging Allows Detection of Aplastic Lesions in a Mouse Model of Breast Cancer

The expression of claudin-4, a protein involved in tight junction complexes, is widely dysregulated in epithelial malignancies. Claudin-4 is overexpressed in several premalignant precursor lesions, including those of cancers of the breast, pancreas, and prostate, and is associated with poor survival. A noncytotoxic C-terminal fragment of Clostridium perfringens enterotoxin (cCPE) is a natural ligand for claudin-4. Here, we demonstrate whole-body quantitative SPECT imaging of preneoplastic breast cancer tissue using 111In-labeled cCPE. Methods: cCPE.GST or GST (GST is glutathione S-transferase) was conjugated to the metal ion chelator benzyl-diethylenetriaminepentaacetic acid to allow 111In radiolabeling. The affinity of radiolabeled cCPE.GST for claudin-4 was confirmed using claudin-4–expressing MDA-MB-468 and SQ20b cells, compared with claudin-4–negative HT1080 cells. In vivo SPECT imaging was performed using athymic mice bearing MDA-MB-468 or HT1080 xenografts and using genetically modified BALB/neuT mice, which spontaneously develop claudin-4–expressing breast cancer lesions. Results: The uptake of 111In-cCPE.GST in claudin-4–positive MDA-MB-468 xenograft tumors in athymic mice was significantly higher than in 111In-GST or claudin-4–negative HT1080 tumors (6.72 ± 0.18 vs. 3.88 ± 1.00 vs. 2.36 ± 1.25 percentage injected dose per gram [%ID/g]; P < 0.0001). No other significant differences were observed in any of the examined organs. BALB/neuT mice, expressing rat neuT under mmtv promotor control, spontaneously developed tumorous lesions within their mammary fat pads over the course of 130 d. Overt mammary tumors were claudin-4–positive, and 111In-cCPE.GST uptake was 3.2 ± 0.70 %ID/g, significantly higher than 111In-GST (1.00 ± 0.60 %ID/g; P < 0.05). Mammary fat pads in mice aged 80 d bore claudin-4–positive aplastic lesions and accumulated 111In-cCPE.GST (3.17 ± 0.51 %ID/g) but not 111In-GST (0.99 ± 0.39 %ID/g; P < 0.001). Conclusion: Taken together, 111In-cCPE.GST targets claudin-4 expression in frank tumors and preneoplastic tissue, and cCPE imaging may be used as an early detection tool for breast, prostate, and pancreatic cancer.
Does leverage influence banks' non-performing loans? Evidence from India

The study examines the association between corporate leverage and banks’ non-performing loans. Using data on Indian manufacturing sector in India for 1993–2004, the findings indicate lagged leverage to be an important determinant of bad loans of banks. In terms of magnitudes, a 10 percentage point rise in the corporate leverage is, on average, associated with 1.3 percentage point rise in sticky loans relative to loans, after a one period lag. In terms of policy implications, the analysis suggests that the leverage ratio can serve as a useful signpost of asset quality and second, the analysis points to the need to improve the collection of data from the corporate sector.
Using Temporal Association Rule Mining to Predict Dyadic Rapport in Peer Tutoring

Social relationships, such as interpersonal closeness or rapport, can lead to improved student learning, but such dynamic, interpersonal phenomena can be diﬃcult for educational support technologies to detect. In this paper, we describe an approach for rapport detection in peer tutoring, using temporal association rules learned from nonverbal, social, and on-task verbal behaviors. From a corpus of 60 hours of annotated multimodal peer tutoring data, we learn the temporal association between behaviors and the rapport score for each 30-second “thin-slice”. We then train a stacked ensemble classiﬁcation model on those association rules and evaluate our ability to reliably predict rapport us-ing multimodal behavioral data. We ﬁnd that our approach allows us to predict rapport well above chance, and more accurately than two baseline models. We are able to predict high rapport more accurately for strangers and low rapport more accurately for friends, which we believe holds promise for the integration of rapport detection into collaborative learning supports and intelligent tutoring systems.
Effect of DNA Methylation on 18S rRNA Gene Sequences during Culture of Taxus chinensis Cells

Cell suspension culture has rapidly become an alternative source of taxol, an anticancer compound. To investigate the role of DNA methylation in the cultural course of Taxus chinensis cells, analyses of 18S rRNA gene sequences of cultured T. chinensis cells and related species were conducted. The phylogenetic analysis of 18S rRNA gene sequences indicated that HG-1 (the cultured T. chinensis cells), like T. mairei (the natural variety of T. chinensis), should be a new variety of T. chinensis, and cell culture can change the 18S rRNA gene sequence at the level of species despite 18S rRNA is the most conserved gene. The analyses of the CpG and TpG+CpA relative abundance and GC content of the 18S rRNA gene sequences made clear that DNA methylation contributed to changes of the 18S rRNA gene sequence of HG-1 at the level of species, which can make HG-1 to become a new variety of T. chinensis.
Multicenter study of banked third-party virus-specific T cells to treat severe viral infections after hematopoietic stem cell transplantation.

Virus-specific T cell (VST) lines could provide useful antiviral prophylaxis and treatment of immune-deficient patients if it were possible to avoid the necessity of generating a separate line for each patient, often on an emergency basis. We prepared a bank of 32 virus-specific lines from individuals with common HLA polymorphisms who were immune to Epstein-Barr virus (EBV), cytomegalovirus, or adenovirus. A total of 18 lines were administered to 50 patients with severe, refractory illness because of infection with one of these viruses after hematopoietic stem cell transplant. The cumulative rates of complete or partial responses at 6 weeks postinfusion were 74.0% (95% CI, 58.5%-89.5%) for the entire group (n = 50), 73.9% (95% CI, 51.2% -96.6%) for cytomegalovirus (n = 23), 77.8% for adenovirus (n = 18), and 66.7% (95% CI, 36.9%-96.5%) for EBV (n = 9). Only 4 responders had a recurrence or progression. There were no immediate infusion-related adverse events, and de novo graft-versus-host disease developed in only 2 patients. Despite the disparity between the lines and their recipients, the mean frequency of VSTs increased significantly postinfusion, coincident with striking decreases in viral DNA and resolution of clinical symptoms. The use of banked third-party VSTs is a feasible and safe approach to rapidly treat severe or intractable viral infections after stem cell transplantation. This study is registered at www.clinicaltrials. gov as NCT00711035.
Single rice growth period was prolonged by cultivars shifts, but yield was damaged by climate change during 1981–2009 in China, and late rice was just opposite

Based on the crop trial data during 1981–2009 at 57 agricultural experimental stations across the North Eastern China Plain (NECP) and the middle and lower reaches of Yangtze River (MLRYR), we investigated how major climate variables had changed and how the climate change had affected crop growth and yield in a setting in which agronomic management practices were taken based on actual weather. We found a significant warming trend during rice growing season, and a general decreasing trend in solar radiation (SRD) in the MLRYR during 1981–2009. Rice transplanting, heading, and maturity dates were generally advanced, but the heading and maturity dates of single rice in the MLRYR (YZ_SR) and NECP (NE_SR) were delayed. Climate warming had a negative impact on growth period lengths at about 80% of the investigated stations. Nevertheless, the actual growth period lengths of YZ_SR and NE_SR, as well as the actual length of reproductive growth period (RGP) of early rice in the MLRYR (YZ_ER), were generally prolonged due to adoption of cultivars with longer growth period to obtain higher yield. In contrast, the actual growth period length of late rice in the MLRYR (YZ_LR) was shortened by both climate warming and adoption of early mature cultivars to prevent cold damage and obtain higher yield. During 1981–2009, climate warming and decrease in SRD changed the yield of YZ_ER by −0.59 to 2.4%; climate warming during RGP increased the yield of YZ_LR by 8.38–9.56%; climate warming and decrease in SRD jointly reduced yield of YZ_SR by 7.14–9.68%; climate warming and increase in SRD jointly increased the yield of NE_SR by 1.01–3.29%. Our study suggests that rice production in China has been affected by climate change, yet at the same time changes in varieties continue to be the major factor driving yield and growing period trends.
PCSD: a plant chromatin state database

Abstract Genome-wide maps of chromatin states have become a powerful representation of genome annotation and regulatory activity. We collected public and in-house plant epigenomic data sets and applied a Hidden Markov Model to define chromatin states, which included 290 553 (36 chromatin states), 831 235 (38 chromatin states) and 3 936 844 (26 chromatin states) segments across the whole genome of Arabidopsis thaliana, Oryza sativa and Zea mays, respectively. We constructed a Plant Chromatin State Database (PCSD, http://systemsbiology.cau.edu.cn/chromstates) to integrate detailed information about chromatin states, including the features and distribution of states, segments in states and related genes with segments. The self-organization mapping (SOM) results for these different chromatin signatures and UCSC Genome Browser for visualization were also integrated into the PCSD database. We further provided differential SOM maps between two epigenetic marks for chromatin state comparison and custom tools for new data analysis. The segments and related genes in SOM maps can be searched and used for motif and GO analysis, respectively. In addition, multi-species integration can be used to discover conserved features at the epigenomic level. In summary, our PCSD database integrated the identified chromatin states with epigenetic features and may be beneficial for communities to discover causal functions hidden in plant chromatin.
Hierarchical LSTM for Sign Language Translation

Continuous Sign Language Translation (SLT) is a challenging task due to its specific linguistics under sequential gesture variation without word alignment. Current hybrid HMM and CTC (Connectionist temporal classification) based models are proposed to solve frame or word level alignment. They may fail to tackle the cases with messing word order corresponding to visual content in sentences. To solve the issue, this paper proposes a hierarchical-LSTM (HLSTM) encoder-decoder model with visual content and word embedding for SLT. It tackles different granularities by conveying spatio-temporal transitions among frames, clips and viseme units. It firstly explores spatio-temporal cues of video clips by 3D CNN and packs appropriate visemes by online key clip mining with adaptive variable-length. After pooling on recurrent outputs of the top layer of HLSTM, a temporal attention-aware weighting mechanism is proposed to balance the intrinsic relationship among viseme source positions. At last, another two LSTM layers are used to separately recurse viseme vectors and translate semantic. After preserving original visual content by 3D CNN and the top layer of HLSTM, it shortens the encoding time step of the bottom two LSTM layers with less computational complexity while attaining more nonlinearity. Our proposed model exhibits promising performance on singer-independent test with seen sentences and also outperforms the comparison algorithms on unseen sentences.
Correlations, Return and Volatility Spillovers in Indian Exchange Rates

This study explores the dynamic nature of return, volatility and correlation transmission mechanism among Indian exchange rates relative to US dollar (USD), Great Britain pound (GBP), euro and Japanese yen. We make use of the dynamic conditional correlation (DCC) vector autoregressive multivariate generalized autoregressive conditional heteroskedasticity (VAR (1)-MVGARCH) model which is capable of capturing the interactive dynamics in the first moment and the second moment of the time series. Our empirical results point to a significant unidirectional return spillover from euro and Japanese yen to USD and bidirectional return spillover between GBP and Japanese yen. We also find evidence of significant volatility spillover effect from USD to GBP, euro and Japanese Yen and from GBP and Euro to USD. Moreover, we find that the time-varying conditional correlations between exchange rate changes dynamically over time and are widely distributed with higher volatility during the period of global financial crisis for all USD and other exchange rate pairs.