Miracle-dz/UniFAR-FTUs huggingface dataset:
5. Systems biology guided by Chinese Medicine reveals new markers for sub-typing rheumatoid arthritis patients

Background. Complex chronic diseases such as rheumatoid arthritis have become a major challenge in medicine and for the pharmaceutical industry. New impulses for drug development are needed. Objective. A systems biology approach is explored to find sub-types of rheumatoid arthritis patients enabling a development towards more personalized medicine. Methods. Blood samples of 33 RA patients and 16 healthy volunteers were collected. The RA patients were diagnosed according to CM theory and divided into two groups, the RA Heat and RA Cold group. CD4+ T-cells were used for a total gene expression analysis. Metabolite profiles were measured in plasma using gas chromatography/mass spectrometry (GC/MS). Multivariate statistics was employed to find potential biomarkers for the RA Heat and RA Cold phenotype. A comprehensive biological interpretation of the results is discussed. Results. The genomics and metabolomics analysis showed statistically relevant different gene expression and metabolite profiles between healthy controls and RA patients as well as between the RA Heat and RA Cold group. Differences were found in the regulation of apoptosis. In the RA Heat group caspase 8 activated apoptosis seems to be stimulated while in the RA Cold group apoptosis seems to be suppressed through the Nrf2 pathway. Conclusions. Rheumatoid arthritis patients could be divided in two groups according to CM theory. Molecular differences between the RA Cold and RA Heat groups were found which suggest differences in apoptotic activity. Subgrouping of patients according to CM diagnosis has the potential to provide opportunities for better treatment outcomes by targeting Western or CM treatment to specific groups of patients. Based on: van Wietmarschen H, Yuan K, Lu C, Gao P, Wang J, Xiao C, Yan X, et al. (2009) Systems biology guided by Chinese medicine reveals new markers for sub-typing rheumatoid arthritis patients. Journal of clinical rheumatology 15(7): 330-7.
A possible formation scenario for dwarf spheroidal galaxies - I. Fiducial model

We perform numerical simulations to study a formation scenario for dwarf spheroidal (dSph) galaxies in which their stellar populations are the products of the dissolution of open star clusters and stellar associations within cosmological dark matter haloes. This paper shows that this process gives rise to objects which resemble the observed dSph satellites of the Milky Way without invoking external influences. The presence of long-lived kinematic substructures within the stellar components of these objects affects their projected velocity dispersions. We find that this in turn affects mass estimates based on the projected velocity dispersion profiles which may overestimate the actual dark matter halo mass depending on the amount of substructure which is present. Our models make predictions about the detailed kinematic and photometric properties of the dSphs which can be tested using future observations.
Data-Driven Adaptive Optimal Tracking Control for Completely Unknown Systems

In this paper, an online data-driven based solution is developed for linear quadratic tracking (LQT) problem of linear systems with completely unknown dynamics. By applying the vectorization operator and Kronecker product, an adaptive identifier is first built to identify the unknown system dynamics, where a new adaptive law with guaranteed convergence is proposed. By using system augmentation method and introducing a discounted factor in the cost function, a compact form of LQT formulation is proposed, where the feedforward and feedback control actions can be obtained simultaneously. Finally, a new policy iteration is introduced to solve the derived augmented algebraic Riccati equation (ARE). Simulation results are presented to demonstrate the effectiveness of the proposed algorithm.
A geometric approach to on-diagonal heat kernel lower bounds on groups

We introduce a new method for obtaining heat kernel on-diagonal lower bounds on noncompact Lie groups and on infinite discrete groups. By using this method, we are able to recover the previously known results for unimodular amenable Lie groups as well as for certain classes of discrete groups including the polycyclic groups, and to give them a geometric interpretation. We also obtain new results for some discrete groups which admit the structure of a semi-direct product or of a wreath product. These include the two-generators groups
Coping With Workplace Stress: A Multiple-Group Comparison of Female Managers and Clerical Workers

This study cross-validated and refined a causal model of workplace stress (B. C. Long, S. E. Kahn, & R. W. Scnutz, 1992). Multivariate analysis of variance and multiple-group structural equation modeling were used to contrast female clerical workers (n = 214) with the original sample of managerial women (n = 249). Consistent with the effects of social roles, clerical workers had fewer coping resources, appraised the stress event as less controllable, experienced more work demands and less support, used relatively less engagement coping, and were more distressed and less satisfied than managers. Moreover, the personality disposition of agentic traits had a stronger influence on coping strategies for clerical workers than for managers. Although recent research has aimed at the development of integrative models of the stress and coping process of employed women (B. C. Long, Kahn, & Schutz, 1992; Portello, 1996; Terry, Tonge, & Callan, 1995), little attention has been paid to the impact of institutional ized social roles on women's experience of work stress. Pearlin (1989) posited that greater vulnerability to stress may be attributable to social roles that reflect the "unequal distribution of resources, opportunities, and self-regard" (p. 245). Ironically, women in management and professional occupations have been the focus of considerable research that has examined the impact of work-related stress on adjustment
Contraceptive use among illiterate women in India: does proximate illiteracy matter?

Illiterate women comprise a particularly vulnerable section of the community. They lack empowerment, are unable to voice their choice with respect to contraceptive use, and also lack access to health services. However, their lack of literacy may be compensated if their partners are literate. Contraceptive use of such illiterate women (proximate literates), may be higher than that of illiterate women whose partners too are illiterates (isolate illiterates). The study uses the third wave of the Demographic Health Survey data for India (2005-2006). The 34,108 currently married illiterate women for whom data is available in the Individual file was divided into two groups, based on whether their partners were literate. Current use of modern contraceptives was compared between these two groups for socio-economic and demographic correlates. This was followed by multivariate analysis based on a logit model. Current use of modern methods was regressed on a dummy representing whether the partner was literate, along with relevant control variables. The results of the All-India (Rural+Urban) and All-India (Rural) models indicated that literacy of partners did lead to a significantly higher level of use of modern contraceptive methods. For the urban sub-sample, however, the study failed to find any significant transmission of information from the literate partner to the respondents. Disaggregate-level analysis also revealed that such transmission was restricted to only specific situations and communities. The study argued that the results may be explained by: [a] Reluctance of the male partner to share information; [b] Lack of information about family planning methods, even when there is communication; and [c] Presence of alternative channels of information reducing dependence of illiterate women on her partner. There should be an attempt to increase information of both partners through face to face interaction, rather than relying solely on public media. Simultaneously, women should be encouraged to develop contacts outside her household as this can reduce her dependence of partner for family planning related knowledge.
Reconsidering Human Capacity for Location-Aware Audio Pattern Recognition: A Case for Immersive Exocentric Sonification

The following paper presents a cross-disciplinary snapshot of 21st century research in sonification and leverages the review to identify a new immersive exocentric approach to studying human capacity to perceive spatial aural cues. The paper further defines immersive exocentric sonification, highlights its unique affordances, and presents an argument for its potential to fundamentally change the way we understand and study the human capacity for location-aware audio pattern recognition. Finally, the paper describes an example of an externally funded research project that aims to tackle this newfound research whitespace.
Migration and welfare state spending

Is international migration a threat to the redistributive programmes of destination countries? Existing work is divided. This paper examines the manner and extent to which increases in immigration are related to welfare state retrenchment, drawing on data from 1970 to 2007. The paper makes three contributions: (1) it explores the impact of changes in immigration on social welfare policy over both the short and medium term; (2) it examines the possibility that immigration matters for spending not just directly, but indirectly, through changes in demographics and/or the labour force; and (3) by disaggregating data on social expenditure into subdomains (including unemployment, pensions, and the like), it tests the impact of immigration on different elements of the welfare state. Results suggest that increased immigration is indeed associated with smaller increases in spending. The major pathway is through impact on female labour force participation. The policy domains most affected are ones subject to moral hazard, or at least to rhetoric about moral hazard.
Pullback attractors for the non-autonomous 2D Navier--Stokes equations for minimally regular forcing

This paper treats the existence of pullback attractors for the non-autonomous 2D Navier--Stokes equations in two different spaces, namely $L^2$ and $H^1$. The non-autonomous forcing term is taken in $L^2_{\rm loc}(\mathbb R;H^{-1})$ and $L^2_{\rm loc}(\mathbb R;L^2)$ respectively for these two results: even in the autonomous case it is not straightforward to show the required asymptotic compactness of the flow with this regularity of the forcing term. Here we prove the asymptotic compactness of the corresponding processes by verifying the flattening property -- also known as ``Condition (C)". We also show, using the semigroup method, that a little additional regularity -- $f\in L^p_{\rm loc}(\mathbb R;H^{-1})$ or $f\in L^p_{\rm loc}(\mathbb R;L^2)$ for some $p>2$ -- is enough to ensure the existence of a compact pullback absorbing family (not only asymptotic compactness). Even in the autonomous case the existence of a compact absorbing set for this model is new when $f$ has such limited regularity.
Precision and linearity of analog temperature sensors for industrial IoT devices

Temperature measurement still presents specific challenges in embedded systems. Since off the shelf microcontrollers also include simple analog inputs, they are widely used in embedded IIoT (Industrial Internet of Things) devices. The analog inputs of such controllers typically have a low resolution, not appropriate for measuring the output of special purpose sensors (e.g., Negative Temperature Coefficient-(NTC)). This paper analyses and compares methods for temperature measurement based on signal conditioning and linearization circuits for thermocouple, NTC, RTD (Resistance Temperature Detector) and semiconductor sensors, offering a set of experimental results obtained without initial calibration or any other software compensation of the initial errors.
Capturing the Risk Premium of Commodity Futures: The Role of Hedging Pressure

We construct long–short factor mimicking portfolios that capture the hedging pressure risk premium of commodity futures. We consider single sorts based on the open interests of hedgers or speculators, as well as double sorts based on both positions. The long–short hedging pressure portfolios are priced cross-sectionally and present Sharpe ratios that systematically exceed those of long-only benchmarks. Further tests show that the hedging pressure risk premiums rise with the volatility of commodity futures markets and that the predictive power of hedging pressure over cross-sectional commodity futures returns is different from the previously documented forecasting power of past returns and the slope of the term structure.
Aptness and beauty in metaphor

abstract Metaphors are comparisons that link dissimilar conceptual domains. We hypothesized that the aptness of a metaphor is linked to the reader’s experience of beauty, and that age and expertise influence these aesthetic judgments. We had young adults, literary experts, and elderly adults rate metaphors for beauty or aptness. Experimental materials consisted of single-sentence novel metaphors whose familiarity, figurativeness, imageability, interpretability, and overall valence ratings were known. Results suggest that beauty and aptness of metaphors are linked for elderly adults but are orthogonal for young adults and literary experts. Elderly participants seem to conflate emotional content with aptness. Young adults are most swayed by a perceived feeling of familiarity when rating for aptness, but not for beauty. Literary experts are relatively unaffected by the psycholinguistic variables, suggesting an emotionally distanced approach to these sentences. Individual differences in literary training and life experience have varying effects on the aesthetic experience of metaphor in regard to beauty and aptness.
Markers of Myocardial Ischemia in Patients with Diabetes Mellitus andSevere Obstructive Sleep Apnea Ã¢ÂÂ Impact of Continuous Positive AirwayPressure Therapy

Introduction: Diabetes Mellitus (T2DM) and obstructive sleep apnea (OSA) are common disorders that often coexist. Both disorders are associated with an increased risk of cardiovascular complications. Repeated nocturnal hypoxia in diabetic patients suffering also from OSA may result in myocardial ischemia. We evaluated whether myocardial ischemia is detectable by ST-segment depression and elevation of high sensitive Troponin T (hs-cTnT) and N-terminal pro B-type natriuretic peptide (NT-proBNP). We also examined the effect of continuous positive airway pressure treatment (CPAP) on these markers. Methods: Fifteen patients with OSA and concomitant T2DM and 26 patients with OSA alone underwent polysomnography at baseline and under CPAP. Blood samples for hs-cTnT and NT-proBNP measurements were drawn prior and immediately after sleep. ST-segment depression was measured at the time of maximum oxygen desaturation during sleep. Results: The apnea-hypopnea-index and oxygen saturation nadir were similar in both groups. Levels of hscTnT and NT-proBNP did not differ significantly before and after baseline polysomnography and CPAP respectively within the same group. But hs-cTnT levels were significantly higher before and after PSG and CPAP respectively in patients suffering from T2DM and OSA compared to patients with OSA alone. In both groups, we found no significant ST-segment depression at the time of oxygen saturation nadir. Conclusions: Despite the fact that patients with T2DM and coexisting OSA experienced severe nocturnal hypoxemia we were unable to detect myocardial ischemia or myocyte necrosis evidenced by significant ST-segment depression or elevation of hs-cTnT and NT-proBNP respectively. CPAP had no influence on hs-cTnT and NTproBNP levels
Banking the Unbanked: Evidence from Three Countries - Working Paper 440

We experimentally test the impact of expanding access to basic bank accounts in Uganda, Malawi, and Chile. Over two years, 17 percent, 10 percent, and 3 percent of treatment individuals made five or more deposits, respectively. Average monthly deposits for them were at the 79th, 91st, and 96th percentiles of baseline savings. Survey data show no clearly discernible intention-to-treat effects on savings or any downstream outcomes. This suggests that policies merely focused on expanding access to basic accounts are unlikely to improve welfare noticeably since impacts, even if present, are likely small and diverse.
Plasma-induced alignment of carbon nanotubes

Uniform films of well-aligned carbon nanotubes have been grown using microwave plasma-enhanced chemical vapor deposition. It is shown that nanotubes can be grown on contoured surfaces and aligned in a direction always perpendicular to the local substrate surface. The alignment is primarily induced by the electrical self-bias field imposed on the substrate surface from the plasma environment. It is found that switching the plasma source off effectively turns the alignment mechanism off, leading to a smooth transition between the plasma-grown straight nanotubes and the thermally grown “curly” nanotubes. The nanotubes grow at a surprisingly high rate of ∼100 nm/s in our plasma process, which may be important for large-scale commercial production of nanotubes.
Investigation statistics of bipolar multilevel memristive mechanism and characterizations in a thin FeOx transition layer of TiN/SiO2/FeOx/Fe structure

We investigated multilevel resistance switching characteristics of the thin FeOx transition layer in a TiN/SiO2/FeOx/Fe structure by controlling the current compliance and stopped voltage during the set and reset processes, respectively. It is observed that the resistive state could be easily tunable by controlling external electric conditions. The multilevel memristive mechanism was characterized by distinguishing the electrical behaviors statistically, inferring that the reset process is associated with the mobile-ion-assisted electrochemical redox. Moreover, the set process is also modeled by power dissipation behaviors. The presented mathematical and physical model provides a possibility to elucidate a universal mechanism for bipolar multilevel memristor.
Relative Attribute Learning with Deep Attentive Cross-image Representation

In this paper, we study the relative attribute learning problem, which refers to comparing the strengths of a specific attribute between image pairs, with a new perspective of crossimage representation learning. In particular, we introduce a deep attentive cross-image representation learning (DACRL) model, which first extracts single-image representation with one shared subnetwork, and then learns attentive cross-image representation through considering the channel-wise attention of concatenated single-image feature maps. Taking a pair of images as input, DACRL outputs a posterior probability indicating whether the first image in the pair has a stronger presence of attribute than the second image. The whole network is jointly optimized via a unified end-to-end deep learning scheme. Extensive experiments on several benchmark datasets demonstrate the effectiveness of our approach against the state-of-the-art methods.
Predictors of Malignancy in Patients with Solitary and Multiple Thyroid Nodules

Introduction: Ultrasound (US) and Fine-needle aspiration (FNA) are the main methods used for investigating thyroid nodules, with questionable predictive values in multinodular goiter (MNG) compared to solitary thyroid nodule (STN). Objective: To detect the independent predictors of malignancy in patients with solitary and multiple nodules. Patients and Methods: Medical records of patients who were admitted for thyroidectomy at Alexandria Main University Hospital and Medical Research Institute Hospital between January 2014 and January 2016 were reviewed. Demographic and clinical data, US reports, FNA reports (Bethesda “B” system), and final histopathological results were recorded and analyzed. Patients with hyper- or hypo-thyroidism, previous history of thyroid cancer or those with incomplete data were excluded. Results: Collectively, 20% (111/554) of the study population proved to have malignancyon final histopathology, 19.3% (82/422) with MNG and 22% (29/132) with a STN. Combining gender and age showed that significantly more male patients with MNG under the age of 45 years had thyroid cancer (X2=11.75, p=0.003). Statistically significant US features in the MNG Group included micro-calcifications, solid composition, echogenicity, incomplete halo, ill-defined margins, and suspicious cervical lymph nodes (LNs). In STN, significant US features included complex composition of nodules, peri-nodular vascularity, and also suspicious cervical LNs. The FNA results of BII-V reports showed that 16.9% (69/408) and 17.6% (22/125) of patients with MNG and STN, respectively, had false negative results. The risk of malignancy showed a significant rise from BIV to BVI lesions in both Groups. Multivariate analysis revealed that, in MNG, the highest malignancy predictor was micro calcification, followed by FNA (BVI) and then suspicious cervical LNs. In STN, the features that retained significance in multivariate analysis were suspicious LNs& BVI-FNA. Conclusion: Based on the data presented, it may be concluded that the independent predictors of malignancy were US findings of micro-calcification in patients with MNG, suspicious cervical LNs and Bethesda VI on FNA in patients with both MNG and STN.
TVT: Two-View Transformer Network for Video Captioning

Video captioning is a task of automatically generating the natural text description of a given video. There are two main challenges in video captioning under the context of an encoder-decoder framework: 1) How to model the sequential information; 2) How to combine the modalities including video and text. For challenge 1), the recurrent neural networks (RNNs) based methods are currently the most common approaches for learning temporal representations of videos, while they suffer from a high computational cost. For challenge 2), the features of different modalities are often roughly concatenated together without insightful discussion. In this paper, we introduce a novel video captioning framework, i.e., Two-View Transformer (TVT). TVT comprises of a backbone of Transformer network for sequential representation and two types of fusion blocks in decoder layers for combining different modalities effectively. Empirical study shows that our TVT model outperforms the state-of-the-art methods on the MSVD dataset and achieves a competitive performance on the MSR-VTT dataset under four common metrics.