Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliable Future Climatic Projections for Sustainable Hydro-Meteorological Assessments in the Western Lake Erie Basin

Modeling efforts to simulate hydrologic processes under different climate conditions rely on accurate input data. Among other inaccuracies, errors in climate projections can lead to incorrect decisions. This study aimed to develop a reliable climate (precipitation and temperature) database for the Western Lake Erie Basin for the 21st century. Two statistically downscaled bias-corrected sources of climate projections (GDO: Global Downscaled Climate and Hydrology Projections and MACA: Multivariate Adaptive Constructed Analogs) were tested for their effectiveness in simulating historic climate (1966–2005) using ground-based station data from the National Climatic Data Center. MACA was found to have less bias than GDO and was better at simulating selected climate indices; thus, its climate projections were subsequently tested with different bias correction methods including the power transformation method, variance scaling of temperature, and Stochastic Weather Generators. The power transformation method outperformed the other methods and was used in bias corrections for 2006 to 2099. From the analysis, mean daily precipitation values were expected to remain more or less the same under both RCP (Representative Concentration Pathway) 4.5 and RCP 8.5 scenarios, ranging between 2.4 mm and 3.2 mm, while standard deviations were expected to increase, pointing to a rescaling of the distribution. Maximum one-day precipitation was expected to increase and could vary between 120 and 650 mm across the basin, while the number of wet days could potentially increase under the effects of RCP 4.5 and RCP 8.5. Both mean maximum and mean minimum daily air temperatures were expected to increase by up to 5.0 °C across the basin, while absolute maximum and minimum values could increase by more than 10 °C. The number of days in which precipitation could potentially fall as snow was expected to decrease, as was the annual number of days for optimal corn growth, although an earlier start to the growing season could be expected. Results from this study were very useful in creating a reliable climate database for the entire Western Lake Erie Basin (WLEB), which can be used for hydrologic, water resources, and other applications in the basin. The resulting climate database is published and accessible through the Purdue University Research Repository (Mehan et al., 2019), which is an open-access repository.
Innovation and Market Structure in the Manufacturing Sector: An Application of Linear Feedback Models

In recent years, there has been a renewed interest in the relationship between market structure and innovation activities at an industry level. The paper examines the relationship between these for the manufacturing sector in a sample of 33 countries. It applies a recently developed method, based on linear feedback models, and uses cross-country time-series data. Despite the relatively small number of observations, the results indicate that domestic competition, external market share, and research and development have a positive effect on innovation activities. The results also suggest that the introduction of the foreign competition may have an initial positive effect on innovation activities, but over time this becomes dissipated.
Incentive Design for Operations-Marketing Multitasking

A firm hires an agent (e.g., a store manager) to undertake both operational and marketing tasks. Marketing tasks boost demand, but for demand to translate into sales, operational effort is required to maintain adequate inventory. The firm designs a compensation plan to induce the agent to put effort into both marketing and operations while facing demand censoring (i.e., demand in excess of available inventory is unobservable). We formulate this incentive-design problem in a principal-agent framework with a multitasking agent subject to a censored signal. We develop a bang-bang optimal control approach, with a general optimality structure applicable to a broad class of incentive-design problems. Using this approach, we characterize the optimal compensation plan, with a bonus region resembling a “mast” and “sail” such that a bonus is paid when either all inventory above a threshold is sold or the sales quantity meets an inventory-dependent target. The optimal mast-and-sail compensation plan implies nonmonotonicity, where the agent can be less likely to receive a bonus for achieving a better outcome. This gives rise to an ex post moral hazard issue where the agent may “hide” inventory to earn a bonus. We show that this ex post moral hazard issue is a result of demand censoring. If available information includes a waiting list (or other noisy signals) to gauge unsatisfied demand, no ex post moral hazard issues remain. This paper was accepted by Vishal Gaur, operations management.
Copper deficiency alters shoot architecture and reduces fertility of both gynoecium and androecium in Arabidopsis thaliana

Copper deficiency reduces plant growth, male fertility and seed set. The contribution of copper to female fertility and the underlying molecular aspects of copper deficiency-caused phenotypes are not well-known. We show that among copper deficiency-caused defects in Arabidopsis thaliana were the increased shoot branching, delayed flowering and senescence, and entirely abolished gynoecium fertility. The increased shoot branching of copper-deficient plants was rescued by the exogenous application of auxin or copper. The delayed flowering was associated with the decreased expression of the floral activator, FT. Copper deficiency also decreased the expression of senescence-associated genes, WRKY53 and SAG13, but increased the expression of SAG12. The reduced fertility of copper-deficient plants stemmed from multiple factors including the abnormal stigma papillae development, the abolished gynoecium fertility, and the failure of anthers to dehisce. The latter defect was associated with reduced lignification, the upregulation of copper microRNAs and the downregulation of their targets, laccases, implicated in lignin synthesis. Copper-deficient plants accumulated ROS in pollen and had reduced cytochrome c oxidase activity in leaves. This study opens new avenues for the investigation into the relationship between copper homeostasis, hormone-mediated shoot architecture, gynoecium fertility and copper deficiency-derived nutritional signals leading to the delay in flowering and senescence. Highlight Copper deficiency alters shoot architecture, delays flowering and senescence, and compromises fertility by altering stigma morphology, disrupting anther lignification and dehiscence, and pollen redox status in Arabidopsis thaliana.
Exploiting the Unbanked: Evidence from Singapore's Unlicensed Moneylending Market

Using a unique dataset covering the borrowing behaviour of over a thousand borrowers, we study the unlicensed moneylending market in Singapore. In this market, borrowers search for lenders, and lenders decide how much profit to extract from borrowers. Lenders harass borrowers into compliance. We observe that different lenders apply different markups on different borrowers. Higher markups discourage borrowers from repeatedly borrowing from a particular lender. Increased enforcement specifically targeted at reducing the number of lenders in this market will increase markups, but will not deter borrowers from becoming recurrent borrowers because they have fewer lenders to choose from.
Model-based learning deficits in compulsivity are linked to faulty representations of task structure

Individuals with higher levels of compulsivity exhibit poorer performance on tasks that require model-based planning but the underlying causes have yet to be established. Here, we sought to determine whether these deficits stem from impoverished action-outcome relational knowledge (i.e. issues building an accurate model of the world) and/or an inability to translate models into action. 192 participants performed a two-step reinforcement learning task with concurrent EEG recordings. We found that representations of task-relevant action-outcome associations reflected in reaction time and parietal-occipital alpha-band power were stronger in individuals whose decisions were more model-based, and critically, were weaker in those high in compulsivity. At the time of choice, mid-frontal theta power, a general marker of cognitive control, was also negatively associated with compulsivity, but not model-based planning. These data suggest that model-based planning deficits in compulsive individuals may arise from failures in building an accurate model of the world.
Electronic Supporting Information EFFECT OF SURFACE CHEMISTRY AND STRUCTURE OF CARBON NANOTUBES ON THE COATING OF GLUCOSE OXIDASE AND ELECTROCHEMICAL BIOSENSORS PERFORMANCE

S.1. 1 Physicochemical characterization Fig. S1 shows the N2 adsorption isotherms for the h-NT and t-NT (with and without oxidation treatment). All materials present type II isotherms with a hysteresis loop. The surface area in these nanostructured materials is mainly defined by their external surface area, but they also have the contribution of the porosity generated by the empty spaces between the tubes.
State-Dependent Cortical Unit Activity Reflects Dynamic Brain State Transitions in Anesthesia

Understanding the effects of anesthesia on cortical neuronal spiking and information transfer could help illuminate the neuronal basis of the conscious state. Recent investigations suggest that the brain state identified by local field potential spectrum is not stationary but changes spontaneously at a fixed level of anesthetic concentration. How cortical unit activity changes with dynamically transitioning brain states under anesthesia is unclear. Extracellular unit activity was measured with 64-channel silicon microelectrode arrays in cortical layers 5/6 of the primary visual cortex of chronically instrumented, freely moving male rats (n = 7) during stepwise reduction of the anesthetic desflurane (6%, 4%, 2%, and 0%). Unsupervised machine learning applied to multiunit spike patterns revealed five distinct brain states. A novel desynchronized brain state with increased spike rate variability, sample entropy, and EMG activity occurred in 6% desflurane with 40.0% frequency. The other four brain states reflected graded levels of anesthesia. As anesthesia deepened the spike rate of neurons decreased regardless of their spike rate profile at baseline conscious state. Actively firing neurons with wide-spiking pattern showed increased bursting activity along with increased spike timing variability, unit-to-population correlation, and unit-to-unit transfer entropy, despite the overall decrease in transfer entropy. The narrow-spiking neurons showed similar changes but to a lesser degree. These results suggest that (1) anesthetic effect on spike rate is distinct from sleep, (2) synchronously fragmented spiking pattern is a signature of anesthetic-induced unconsciousness, and (3) the paradoxical, desynchronized brain state in deep anesthesia contends the generally presumed monotonic, dose-dependent anesthetic effect on the brain. SIGNIFICANCE STATEMENT Recent studies suggest that spontaneous changes in brain state occur under anesthesia. However, the spiking behavior of cortical neurons associated with such state changes has not been investigated. We found that local brain states defined by multiunit activity had a nonunitary relationship with the current anesthetic level. A paradoxical brain state displaying asynchronous firing pattern and high EMG activity was found unexpectedly in deep anesthesia. In contrast, the synchronous fragmentation of neuronal spiking appeared to be a robust signature of the state of anesthesia. The findings challenge the assumption of monotonic, anesthetic dose-dependent behavior of cortical neuron populations. They enhance the interpretation of neuroscientific data obtained under anesthesia and the understanding of the neuronal basis of anesthetic-induced state of unconsciousness.
Understanding Usage Intention of Social Media’s Innovative Functions: Based on Expanded Innovation Diffusion Theory

Drawing upon expanded innovation diffusion theory (IDT), this study investigates the social media users’ usage intention toward its innovative functions. 532 data were collected from the Chinese leading social media—WeChat. The results show that the relative advantage, ease of use, trialability, observability, subjective norm and image have positive effect on users’ usage intention. Whereas compatibility has no significant impact. Based upon these findings, we discussed the theoretical contributions and practical implication of this study
Oscillating and stable genome topologies underlie hepatic physiological rhythms during the circadian cycle

The circadian clock drives extensive temporal gene expression programs controlling daily changes in behavior and physiology. In mouse liver, transcription factors dynamics, chromatin modifications, and RNA Polymerase II (PolII) activity oscillate throughout the 24-hour (24h) day, regulating the rhythmic synthesis of thousands of transcripts. Also, 24h rhythms in gene promoter-enhancer chromatin looping accompany rhythmic mRNA synthesis. However, how chromatin organization impinges on temporal transcription and liver physiology remains unclear. Here, we applied time-resolved chromosome conformation capture (4C-seq) in livers of WT and arrhythmic Bmal1 knockout mice. In WT, we observed 24h oscillations in promoter-enhancer contact at multiple loci including the core-clock genes Period1, Period2 and Bmal1. In addition, we detected rhythmic PolII activity, chromatin modifications and transcription involving stable chromatin loops at gene promoters representing key liver function such as glucose and lipid metabolism and detoxification. Intriguingly, these contacts persisted in clock-impaired mice in which both PolII activity and chromatin marks no longer oscillated. Finally, we observed chromatin interaction hubs connecting neighbouring genes showing coherent transcription regulation across genotypes. Thus, both clock-controlled and clock-independent chromatin topology underlie rhythmic regulation of liver physiology.
Opponent intracerebral signals for reward and punishment prediction errors in humans

Whether maximizing rewards and minimizing punishments rely on distinct brain systems remains debated, inconsistent results coming from human neuroimaging and animal electrophysiology studies. Bridging the gap across species and techniques, we recorded intracerebral activity from twenty patients with epilepsy while they performed an instrumental learning task. We found that both reward and punishment prediction errors (PE), estimated from computational modeling of choice behavior, correlated positively with broadband gamma activity (BGA) in several brain regions. In all cases, BGA increased with both outcome (reward or punishment versus nothing) and surprise (how unexpected the outcome is). However, some regions (such as the ventromedial prefrontal and lateral orbitofrontal cortex) were more sensitive to reward PE, whereas others (such as the anterior insula and dorsolateral prefrontal cortex) were more sensitive to punishment PE. Thus, opponent systems in the human brain might mediate the repetition of rewarded choices and the avoidance of punished choices.
Synthetic observations from deep generative models and binary omics data with limited sample size

Deep generative models can be trained to represent the joint distribution of data, such as measurements of single nucleotide polymorphisms (SNPs) from several individuals. Subsequently, synthetic observations are obtained by drawing from this distribution. This has been shown to be useful for several tasks, such as removal of noise, imputation, for better understanding underlying patterns, or even exchanging data under privacy constraints. Yet, it is still unclear how well these approaches work with limited sample size. We investigate such settings specifically for binary data, e.g., as relevant when considering SNP measurements, and evaluate three frequently employed generative modeling approaches, variational autoencoders (VAEs), deep Boltzmann machines (DBMs) and generative adversarial networks (GANs). This includes conditional approaches, such as when considering gene expression conditional on SNPs. Recovery of pair-wise odds ratios is considered as a primary performance criterion. For simulated as well as real SNP data, we observe that DBMs generally can recover structure for up to 100 variables with as little as 500 observations, with a tendency of over-estimating odds ratios when not carefully tuned. VAEs generally get the direction and relative strength of pairwise relations right, yet with considerable under-estimation of odds ratios. GANs provide stable results only with larger sample sizes and strong pair-wise relations in the data. Taken together, DBMs and VAEs (in contrast to GANs) appear to be well suited for binary omics data, even at rather small sample sizes. This opens the way for many potential applications where synthetic observations from omics data might be useful.
Quantitative Analysis of an Airblast Atomizer in the Near-field Region Using Broadband and Narrowband X-ray Measurements

Airblast atomizers are widely used in many industries including fuel combustion, atomization drying, and spray painting. The quality of the spray, however, has a large impact on the efficiency and effectiveness of the spray process. Understanding the primary breakup mechanism(s) in the near-field region of the spray is critical if one wants to control it to provide better spray characteristics. Traditional optical imaging methods in this region are extremely challenging because the near-field region is generally optically dense. In contrast, X-ray imaging can penetrate the near-field region and provide quantitative measurements to enhance our knowledge of this spray region. In this study, a broadband and narrowband X-ray source were used in the near-field region of a canonical coaxial airblast atomizer. To enhance image contrast with the broadband source, 20% potassium iodide was added to the liquid phase. The narrowband X-ray source was used to determine the equivalent path length because the X-ray absorption coefficient is known exactly for the given monochromatic X-ray beam. These measurements were compared to a calibrated broadband source where a penumbra and beam hardening/ attenuation coefficient correction were needed to provide accurate results.
Salivary AsHPX12 influence pre-blood meal associated behavioral properties in the mosquito Anopheles stephensi

In the adult female mosquito, successful blood meal acquisition is accomplished by salivary glands, which releases a cocktail of proteins to counteract vertebrate host’s immune-homeostasis. However, the biological relevance of many salivary proteins remains unknown. Here, we characterize a salivary specific Heme peroxidase family member HPX12, originally identified from Plasmodium vivax infected salivary RNAseq data of the mosquito Anopheles stephensi. We demonstrate that dsRNA silencing mediated mRNA depletion of salivary AsHPX12 (80-90%), causes enhanced host attraction but reduced blood-meal acquisition abilities, by increasing probing propensity (31%), as well as probing time (100–200s, P<0.0001) as compared to control (35-90s) mosquitoes group. Altered expression of the salivary secretory and antennal proteins may account for an unusual fast release of salivary cocktail proteins, but the slowing acquisition of blood meal, possibly due to salivary homeostasis disruption of AsHPX12 silenced mosquitoes. A parallel transcriptional modulation in response to blood feeding and P. vivax infection, further establish a possible functional correlation of AsHPX12 role in salivary immune-physiology and Plasmodium sporozoites survival/transmission. We propose that salivary HPX12 may have a vital role in the management of ‘pre- and post’-blood meal associated physiological-homeostasis and parasite transmission. Graphical abstract Figure 1: Schematic representation of mosquito’s blood meal acquisition and upshot on blood-feeding after silencing of salivary gland HPX-12. (A) After landing over host skin, mosquito mouthparts (proboscis) actively engaged to search, probe, and pierce the skin followed by a rapid release of the pre-synthesized salivary cocktail, which counteracts the host homeostasis, inflammation, and immune responses, during blood meal uptake. (B) Silencing of HPX-12 disrupts salivary gland homeostasis, enhancing mosquito attraction, possibly by up-regulating odorant-binding proteins genes-OBP-7,10 and OBP-20 expression in the Olfactory System. However, HPX-12 disruption may also cause significant effects on pre-blood meal associated probing abilities, which may be due to fast down-regulation of salivary cocktail proteins such as Anopheline, Apyrase, D7L proteins.
Functional connectivity within and between n-back modulated regions: An adult lifespan PPI investigation

Working memory (WM) and its BOLD-related parametric modulation under load decrease with age. Functional connectivity (FC) generally increases with WM load; however, how aging impacts connectivity and whether this is load-dependent, region-dependent, or associated with cognitive performance is unclear. This study examines these questions in 170 healthy adults (Mage = 52.99 ± 19.18) who completed fMRI scanning during an n-back task (0-, 2-, 3-, and 4-back). FC was estimated utilizing a modified generalized psychophysiological interaction approach with seeds from fronto-parietal (FP) and default mode (DM) regions that modulated to n-back difficulty. FC analyses focused on both connectivity during WM engagement (task vs control) and connectivity in response to increased WM load (linear slope across conditions). Each analysis utilized within- and between-region FC, predicted by age (linear or quadratic), and its associations with in- and out-of-scanner task performance. Engaging in WM either generally (task vs control) or as a function of difficulty strengthened integration within- and between-FP and DM regions. Notably, these task-sensitive functional connections were robust to the effects of age. Stronger negative FC between FP and DM regions was also associated with better WM performance in an age-dependent manner, occurring selectively in middle- and older-adults. These results suggest that FC is critical for engaging in cognitively demanding tasks, and its lack of sensitivity to healthy aging may provide a means to maintain cognition across the adult lifespan. Thus, this study highlights the contribution of maintenance in brain function to support working memory processing with aging. Impact Statement The literature examining functional connectivity (FC) during working memory (WM) in healthy adults is mixed in both age effects and its relationship to performance. This study contributes to the literature by examining a large, adult lifespan sample, increased levels of WM load, and additional investigation of connections within and between fronto-parietal and default mode regions. Results revealed age-invariant strengthened FC during WM, suggesting that healthy aging may be resilient to FC changes. Additionally, negative FC between regions was associated with better WM performance in middle-aged and older adults, highlighting the important of FC maintenance to support successful WM ability.