Miracle-dz/UniFAR-FTUs huggingface dataset:
Hidden Integrality of SDP Relaxation for Sub-Gaussian Mixture Models

We consider the problem of estimating the discrete clustering structures under Sub-Gaussian Mixture Models. Our main results establish a hidden integrality property of a semidefinite programming (SDP) relaxation for this problem: while the optimal solutions to the SDP are not integer-valued in general, their estimation errors can be upper bounded in terms of the error of an idealized integer program. The error of the integer program, and hence that of the SDP, are further shown to decay exponentially in the signal-to-noise ratio. To the best of our knowledge, this is the first exponentially decaying error bound for convex relaxations of mixture models, and our results reveal the "global-to-local" mechanism that drives the performance of the SDP relaxation. A corollary of our results shows that in certain regimes the SDP solutions are in fact integral and exact, improving on existing exact recovery results for convex relaxations. More generally, our results establish sufficient conditions for the SDP to correctly recover the cluster memberships of $(1-\delta)$ fraction of the points for any $\delta\in(0,1)$. As a special case, we show that under the $d$-dimensional Stochastic Ball Model, SDP achieves non-trivial (sometimes exact) recovery when the center separation is as small as $\sqrt{1/d}$, which complements previous exact recovery results that require constant separation.
Accuracy of an oscillometric blood pressure monitor in anesthetized pigs

The purpose of this study is to evaluate the accuracy of an oscillometric blood pressure monitor in anesthetized pigs. Invasive blood pressure (IBP) and noninvasive blood pressure (NIBP) measurements were taken using a DRE Waveline Pro multiparameter monitor at four different time points in 17 pigs undergoing injectable anesthesia. NIBP measurements were taken on both the thoracic and pelvic limbs. Bland Altman analysis was used to assess agreement between methods and a linear mixed-effects model was used to evaluate the effect of cuff position and blood pressure on bias. Invasive systolic arterial pressure (SAP) ranged between 112 and 161 mmHg (mean ± SD: 138.8 ± 13.3; median: 139.5). Invasive diastolic arterial pressure (DAP) ranged between 60 and 104 mmHg (mean ± SD: 86.0 ± 9.1; median: 87.0). Invasive mean arterial pressure (MAP) ranged between 79 and 121 mmHg (mean ± SD: 103.2 ± 9.3; median 103.0). Only the diastolic and mean measurements obtained from the pelvic limb met criteria outlined by the American College of Internal Medicine for required accuracy of NIBP monitors. Bias was significantly higher in the thoracic limb in comparison to the pelvic limb and was significantly higher at blood pressures above median. In general, NIBP measurements underestimated IBP measurements. In conclusion, the use of the DRE Waveline Pro to assess NIBP in anesthetized pigs may be useful in monitoring trends in mean and diastolic blood pressure and is most accurate when used on the pelvic limb.
The Use of Voice Cues for Speaker Gender Recognition in Cochlear Implant Recipients.

PURPOSE The focus of this study was to examine the influence of fundamental frequency (F0) and vocal tract length (VTL) modifications on speaker gender recognition in cochlear implant (CI) recipients for different stimulus types. METHOD Single words and sentences were manipulated using isolated or combined F0 and VTL cues. Using an 11-point rating scale, CI recipients and listeners with normal hearing rated the maleness/femaleness of the corresponding voice. RESULTS Speaker gender ratings for combined F0 and VTL modifications were similar across all stimulus types in both CI recipients and listeners with normal hearing, although the CI recipients showed a somewhat larger ambiguity. In contrast to listeners with normal hearing, F0-VTL and F0-only modifications revealed similar ratings in the CI recipients when using words as stimuli. However, when sentences were used, a difference was found between F0-VTL-based and F0-based ratings. Modifying VTL cues alone did not affect ratings in the CI group. CONCLUSIONS Whereas speaker gender ratings by listeners with normal hearing relied on combined VTL and F0 cues, CI recipients made only limited use of VTL cues, which might be one reason behind problems with identifying the speaker on the basis of voice. However, use of the voice cues depended on stimulus type, with the greater information in sentences allowing a more detailed analysis than single words in both listener groups.
Behavior-aware UAV-assisted crowd sensing technique for urban vehicular environments

Measuring vehicles density and distribution in urban environments is an important task. The results of such estimation are highly required for different applications such as road lights configuration, congestion control, and also inter-vehicle data routing. This task, which is known as crowd sensing, is mostly based on smartphone-assisted sensing. However, in urban environments the multiple kinds of obstacles make it hard and mostly inaccurate especially for RoadSide Units (RSUs) low density cases. Furthermore, the assumption that all vehicles are collaborative and honest can lead to unexpected and unwanted situations. To address the above mentioned problems, we propose in this paper a trust-aware crowd sensing technique based on Unmanned Aerial Vehicle (UAV) for vehicular urban environments. Considering the real traffic information and the distribution of dishonest nodes in the network gathered by UAVs, our proposed solution provides a global view to both vehicles and RSUs, which can be used for different applications such as: finding the shortest and most trusted possible path to messages' final destinations, and also for the intelligent congestion control. Our simulation results show that our solution offers instant crowd and trust information over which in addition to the high detection ratios, also high packet delivery ratios with low network overhead are achieved.
EXAMINING WHAT BEST EXPLAINS CORPORATE CREDIT RISK: ACCOUNTING-BASED VERSUS MARKET-BASED MODELS

Using a sample of 2,186 credit default swap (CDS) spreads quoted in the European market during the period 2002-2009, this paper empirically analyzes which model – accounting- or market-based – better explains corporate credit risk. We find that there is little difference in the explanatory power of the two approaches. Our results suggest that both accounting and market data complement one other and thus that a comprehensive model that includes both types of variables appears to be the best option for explaining credit risk. We also show that the explanatory power of accounting- and market-based variables for measuring credit risk is particularly strong during periods of high uncertainty, as experienced in the recent financial crisis, and that it decreases as the CDS contract matures. Finally, the comprehensive model continues to show the best results when using the credit rating as the proxy for credit risk, but accounting variables currently appear to have a more important role than the market variables
Psychosocial aspects of rosacea with a focus on anxiety and depression

Background Rosacea is a common, chronic skin condition characterized by facial redness and inflammatory lesions. The disease can lead to social stigmatization and may significantly reduce the quality of life of patients. Psychosocial impact of rosacea can be severe and debilitating; however, it is still underestimated. Objective This paper provides a literature review focused on depression and anxiety in patients with rosacea. Conclusion Rosacea patients have an increased risk of developing depression and anxiety and tend to avoid social situations. However, there are still limited data on this condition. Effective treatment of clinical symptoms brings significant improvement in psychological symptoms. Further studies should be conducted to investigate in more detail the psychological impact of rosacea. In addition, improvement of the efficacy of rosacea treatment is still needed.
Scales of Spatial Heterogeneity of Plastic Marine Debris in the Northeast Pacific Ocean

Plastic debris has been documented in many marine ecosystems, including remote coastlines, the water column, the deep sea, and subtropical gyres. The North Pacific Subtropical Gyre (NPSG), colloquially called the “Great Pacific Garbage Patch,” has been an area of particular scientific and public concern. However, quantitative assessments of the extent and variability of plastic in the NPSG have been limited. Here, we quantify the distribution, abundance, and size of plastic in a subset of the eastern Pacific (approximately 20–40°N, 120–155°W) over multiple spatial scales. Samples were collected in Summer 2009 using surface and subsurface plankton net tows and quantitative visual observations, and Fall 2010 using surface net tows only. We documented widespread, though spatially variable, plastic pollution in this portion of the NPSG and adjacent waters. The overall median microplastic numerical concentration in Summer 2009 was 0.448 particles m−2 and in Fall 2010 was 0.021 particles m−2, but plastic concentrations were highly variable over the submesoscale (10 s of km). Size-frequency spectra were skewed towards small particles, with the most abundant particles having a cross-sectional area of approximately 0.01 cm2. Most microplastic was found on the sea surface, with the highest densities detected in low-wind conditions. The numerical majority of objects were small particles collected with nets, but the majority of debris surface area was found in large objects assessed visually. Our ability to detect high-plastic areas varied with methodology, as stations with substantial microplastic did not necessarily also contain large visually observable objects. A power analysis of our data suggests that high variability of surface microplastic will make future changes in abundance difficult to detect without substantial sampling effort. Our findings suggest that assessment and monitoring of oceanic plastic debris must account for high spatial variability, particularly in regards to the evaluation of initiatives designed to reduce marine debris.
Identification of Upregulated Genes under Cold Stress in Cold-Tolerant Chickpea Using the cDNA-AFLP Approach

Low temperature injury is one of the most significant causes of crop damage worldwide. Cold acclimatization processes improve the freezing tolerance of plants. To identify genes of potential importance for acclimatzation to the cold and to elucidate the pathways that regulate this process, global transcriptome expression of the chickpea (Cicer arietinum L), a species of legume, was analyzed using the cDNA-AFLP technique. In total, we generated 4800 transcript-derived fragments (TDFs) using cDNA-AFLP in conjunction with 256 primer combinations. We only considered those cDNA fragments that seemed to be up-regulated during cold acclimatization. Of these, 102 TDFs with differential expression patterns were excised from gels and re-amplified by PCR. Fifty-four fragments were then cloned and sequenced. BLAST search of the GenBank non-redundant (nr) sequence database demonstrated that 77 percent of the TDFs belonged to known sequences with putative functions related to metabolism (31), transport (10), signal transduction pathways (15) and transcription factors (21). The last group of expressed transcripts showed homology to genes of unknown function (22). To further analyze and validate our cDNA-AFLP experiments, the expression of 9 TDFs during cold acclimatzatiion was confirmed using real time RT-PCR. The results of this research show that cDNA-AFLP is a powerful technique for investigating the expression pattern of chickpea genes under low-temperature stress. Moreover, our findings will help both to elucidate the molecular basis of low-temperature effects on the chickpea genome and to identify those genes that could increase the cold tolerance of the chickpea plant.
Seasonal Changes in Metabolism and Cellular Stress Phenomena in the Gilthead Sea Bream (Sparus aurata)

Seasonal temperature changes may take organisms to the upper and lower limit of their thermal range, with respective variations in their biochemical and metabolic profile. To elucidate these traits, we investigated metabolic and antioxidant patterns in tissues of sea bream Sparus aurata during seasonal acclimatization for 1 yr in the field. Metabolic patterns were assessed by determining lactate dehydrogenase, citrate synthase, and β-hydroxyacyl CoA dehydrogenase activities, their kinetic properties and plasma levels of glucose, lactate, and triglycerides and tissue succinate levels. Oxidative stress was assessed by determining antioxidant enzymes superoxide dismutase, catalase, and glutathione reductase activities and levels of thiobarbituric acid reactive substances. Xanthine oxidase (XO) activity was determined as another source of reactive oxygen species (ROS) production. Furthermore, we studied the antiapoptotic protein indicator Bcl-2 and the apoptotic protein indicators Bax, Bad, ubiquitin, and caspase as well as indexes of autophagy (LC3B II/LC3B I and SQSTM1/p62) in the liver and the heart to identify possible relationships between oxidative stress and cell death. The results indicate clear seasonal metabolic patterns involving oxidative stress during summer as well as winter. During cold acclimatization, lipid oxidation is induced, while during increased temperatures, warm-induced metabolic activation and carbohydrate oxidation are observed. Thus, oxidative stress seems to be more prominent during warming because of the increased aerobic metabolism. The seasonal profile of apoptosis and XO as another source of ROS matches the results obtained in the laboratory and are interpreted within the framework of oxygen- and capacity-limited thermal tolerance.
Thai Water Lily Extract Induces B16 Melanoma Cell Apoptosis and Inhibits Cellular Invasion Through the Role of Cellular Oxidants

Melanoma is a cancer that is associated with a high capacity of invasion. Oxidative stress is recognized as cancer growth and progression. The phytochemical pigments of natural products show either anti-oxidant or pro-oxidant activity from the redox system. In addition, the phytophenolics also prevent cancer cell proliferation and progression. Objective: This study aims to investigate the effects of Thai water lily on cell apoptosis and cellular invasion through the role of cellular oxidants in B16 melanoma cells. Methods: The cytotoxicity and cell apoptosis of Thai water lily extract treating B16 cells were performed by using the MTT and Annexin V/PI-flow cytometry methods, respectively. In addition, cellular oxidants and cancer cell invasion were also obtained by using DCFH-DA and Boyden chamber assays, respectively. Results: Thai water lily, Nymphaea stellate extract was shown to be markedly toxic to B16 melanoma cells with IC50 = 814 µg/ml. The extract at 800 and 1,000 µg/ml demonstrated pro-oxidant activity relating to the cell apoptosis. The low concentrations of the extract at 200 and 400 µg/ml showed the anti-oxidant function associated with the inhibitory effect of melanoma cell invasion. Conclusion: Thai water lily extract may play an important role in bioactive work as a chemo preventive agent on the modulation of cellular oxidative stress-induced apoptosis and suppressed cancer cell invasion.
Identifying Mechanisms of Behavior Change in Psychosocial Alcohol Treatment Trials: Improving the Quality of Evidence from Mediational Analyses.

OBJECTIVE In recent years, a shift has occurred from identifying variables that mediate the effects of psychosocial interventions for problematic alcohol use to trying to identify effective mechanisms of behavior change (MOBCs) that lead to better drinking-related and other outcomes. Although implementing interventions targeting specific MOBCs has considerable conceptual and intuitive appeal, it is important that strong empirical evidence be available that supports such implementation. One aim of this article is to consider some prior mediational analyses of the effects of alcohol-focused psychosocial treatments to illustrate findings and the types of evidence that typically have been presented. A second aim is to consider methodological approaches, specifically certain statistical analyses of observational data and experimental designs, that could provide more rigorous evidence regarding the causal effects of mechanisms of change (mediators) in producing desired drinking-related outcomes. RESULTS Prior analyses that have examined the association of a mediator with an outcome, or the relationship between a mediator and an outcome with assigned treatment controlled, do not provide strong evidence regarding the causal effects of mediators on outcomes. Unfortunately, experimental designs that directly manipulate mediators seem difficult to apply in the alcohol treatment field as an approach to examine mediator/MOBC effects. CONCLUSION To produce more compelling evidence, we need to investigate interventions that target a specific MOBC and then capitalize on random assignment to intervention/control conditions by using principal stratification or instrumental variable analyses to identify the effects of intervention-induced mediator change on outcomes.
Genome-Wide Profiling of miRNA and mRNA Expression in Alzheimer’s Disease

Background Our study aimed to identify key differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) which can serve as potential biomarkers for diagnosis and therapy of Alzheimer’s disease (AD). Material/Methods We performed miRNA and mRNA integrated analysis (MMIA) to identify DEGs and DEmiRNAs of AD. The AD-specific DEmiRNAs-targets interaction network was contrasted. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis were performed. Q-RT-PCR was used to verify the expression of selected DEGs and DEmiRNAs. Results We conducted MMIA of AD based on 1 miRNA dataset and 3 mRNA datasets derived from the Gene Expression Omnibus (GEO) database; 1759 DEGs and 12 DEmiRNAs were obtained. DEGs of AD were significantly enriched in Huntington’s disease and AD. LRP1, CDK5R1, PLCβ2, NDUFA4, and DLG4 were 5 DEGs regulated by 4 DEmiRNAs, including miR-26b-5p, miR-26a-5p, miR-107, and miR-103a-3p. These 4 miRNAs were the top 4 miRNAs covering most DEGs. According to the qRT-PCR results, the expression of PLCβ2, NDUFA4, DLG4, miR-107, and miR-103a-3p was consistent with our integrated analysis. Conclusions We concluded that LRP1, CDK5R1, PLCβ2, NDUFA4, and DLG4 may play a role in AD regulated by miR-26b-5p, miR-26a-5p, miR-107, and miR-103a-3p. Our findings will contribute to identification of biomarkers and new strategies for drug design for AD treatment.
Chiron: Privacy-preserving Machine Learning as a Service

Major cloud operators offer machine learning (ML) as a service, enabling customers who have the data but not ML expertise or infrastructure to train predictive models on this data. Existing ML-as-a-service platforms require users to reveal all training data to the service operator. We design, implement, and evaluate Chiron, a system for privacy-preserving machine learning as a service. First, Chiron conceals the training data from the service operator. Second, in keeping with how many existing ML-as-a-service platforms work, Chiron reveals neither the training algorithm nor the model structure to the user, providing only black-box access to the trained model. Chiron is implemented using SGX enclaves, but SGX alone does not achieve the dual goals of data privacy and model confidentiality. Chiron runs the standard ML training toolchain (including the popular Theano framework and C compiler) in an enclave, but the untrusted model-creation code from the service operator is further confined in a Ryoan sandbox to prevent it from leaking the training data outside the enclave. To support distributed training, Chiron executes multiple concurrent enclaves that exchange model parameters via a parameter server. We evaluate Chiron on popular deep learning models, focusing on benchmark image classification tasks such as CIFAR and ImageNet, and show that its training performance and accuracy of the resulting models are practical for common uses of ML-as-a-service.
Assessing the Oral Health Needs of African American Men in Low-Income, Urban Communities

Despite improvements in oral health status in the United States, pronounced racial/ethnic disparities exist. Black men are less likely to visit the dentist, are twice as likely to experience tooth decay, and have a significantly lower 5-year oral cancer survival rate when compared to White men. The Minority Men’s Oral Health Dental Access Program employed a community-based participatory research approach to examine the oral health barriers and opportunities for intervention among Black men in a low-income, urban neighborhood. A cross-sectional study design was implemented through a self-administered survey completed among 154 Black males. The majority reported not having dental insurance (68.8%). Most frequently cited oral health care barriers were lack of dental insurance and not being able to afford dental care. Attitudes related to the significance of dental care centered on cancer prevention and feeling comfortable with one’s smile. The impact of oral health on daily life centered on social interaction, with men citing insecurities associated with eating, talking, and smiling due to embarrassment with how their teeth/mouth looked to others. Multivariate logistic regression revealed that those who had difficulty finding dental care were 4.81 times (odds ratio = 4.65, 95% confidence interval [1.80, 12.85]) more likely to report no dental insurance, and 2.73 times (odds ratio = 3.72; 95% confidence interval [1.12, 6.70]) more likely to report poor oral health. Community-based participatory approaches include assessment of neighborhood residents affected by the health issue to frame interventions that resonate and are more effective. Social, physical, and infrastructural factors may emerge, requiring a multilevel approach.
On the role of ice‐nucleating aerosol in the formation of ice particles in tropical mesoscale convective systems

Over the decades, the cloud physics community has debated the nature and role of aerosol particles in ice initiation. The present study shows that the measured concentration of ice crystals in tropical mesoscale convective systems exceeds the concentration of ice nucleating particles (INPs) by several orders of magnitude. The concentration of INPs was assessed from the measured aerosol particle concentration in the size range of 0.5 to 1 µm. The observations from this study suggest that primary ice crystals formed on INPs make only a minor contribution to the total concentration of ice crystals in tropical mesoscale convective systems. This is found by comparing the predicted INP number concentrations with in situ ice particle number concentrations. The obtained measurements suggest that ice multiplication is the likely explanation for the observed high concentrations of ice crystals in this type of convective system.