Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinct patterns of neural response to faces from different races in humans and deep networks

Abstract Social categories such as the race or ethnicity of an individual are typically conveyed by the visual appearance of the face. The aim of this study was to explore how these differences in facial appearance are represented in human and artificial neural networks. First, we compared the similarity of faces from different races using a neural network trained to discriminate identity. We found that the differences between races were most evident in the fully connected layers of the network. Although these layers were also able to predict behavioural judgements of face identity from human participants, performance was biased toward White faces. Next, we measured the neural response in face-selective regions of the human brain to faces from different races in Asian and White participants. We found distinct patterns of response to faces from different races in face-selective regions. We also found that the spatial pattern of response was more consistent across participants for own-race compared to other-race faces. Together, these findings show that faces from different races elicit different patterns of response in human and artificial neural networks. These differences may underlie the ability to make categorical judgements and explain the behavioural advantage for the recognition of own-race faces.
Simplicial Complex Neural Networks

Graph-structured data, where nodes exhibit either pair-wise or high-order relations, are ubiquitous and essential in graph learning. Despite the great achievement made by existing graph learning models, these models use the direct information (edges or hyperedges) from graphs and do not adopt the underlying indirect information (hidden pair-wise or high-order relations). To address this issue, in this paper, we propose a general framework named Simplicial Complex Neural (SCN) network, in which we construct a simplicial complex based on the direct and indirect graph information from a graph so that all information can be employed in the complex network learning. Specifically, we learn representations of simplices by aggregating and integrating information from all the simplices together via layer-by-layer simplicial complex propagation. In consequence, the representations of nodes, edges, and other high-order simplices are obtained simultaneously and can be used for learning purposes. By making use of block matrix properties, we derive the theoretical bound of the simplicial complex filter learnt by the propagation and establish the generalization error bound of the proposed simplicial complex network. We perform extensive experiments on node (0-simplex), edge (1-simplex), and triangle (2-simplex) classifications, and promising results demonstrate the performance of the proposed method is better than that of existing graph and hypergraph network approaches.
Frequency of fibromyalgia in a cohort of Turkish patients with lung cancer and its effect on pain, sleep quality, fatigue and quality of life

This study aimed to examine the frequency of fibromyalgia (FM) in patients with lung cancer and evaluate its effect on patients’ pain, sleep quality, fatigue, and quality of life parameters. The study was designed as a prospective cross-sectional and a total of 116 lung cancer patients were included. FM classification was made according to the 2016 ACR criteria. All patients were evaluated using a visual analog scale, fibromyalgia impact questionnaire, multidimensional assessment of fatigue, EuroQol 5D scale, Jenkins sleep scale, and Beck depression inventory. Patients were divided into FM-positive and negative groups according to the presence of FM. Demographic and clinical parameters were investigated between the groups. FM was detected in 14 (12.2%) patients. The mean age of the patients was 62.2 ± 8.4 years. There was a male predominance in 93 (80.2%) patients. No statistical difference was found between the groups in terms of body mass index, age, symptom duration, chemotherapy, and radiotherapy history. A statistically significant difference was found between FM positive and negative groups in FIQ, multidimensional assessment of fatigue, JSS, EQ-5D, visual analog scale, and Beck depression inventory scores. FM is seen more frequently in patients with lung cancer and has a negative effect on sleep, quality of life, fatigue, and mental functions. We think that physicians should not ignore the presence of FM when treating patients diagnosed with lung cancer.
High-resolution analysis of bound Ca2+ in neurons and synapses

The amount of bound Ca2+ in neurons correlates significantly to the intensity of markers for GABAergic pre-synapse and glutamatergic post-synapses, and negatively to pre-synaptic activity. Calcium (Ca2+) is a well-known second messenger in all cells, and is especially relevant for neuronal activity. Neuronal Ca2+ is found in different forms, with a minority being freely soluble in the cell and more than 99% being bound to proteins. Free Ca2+ has received much attention over the last few decades, but protein-bound Ca2+ has been difficult to analyze. Here, we introduce correlative fluorescence and nanoscale secondary ion mass spectrometry imaging as a tool to describe bound Ca2+. As expected, bound Ca2+ is ubiquitous. It does not correlate to free Ca2+ dynamics at the whole-neuron level, but does correlate significantly to the intensity of markers for GABAergic pre-synapse and glutamatergic post-synapses. In contrast, a negative correlation to pre-synaptic activity was observed, with lower levels of bound Ca2+ observed in the more active synapses. We conclude that bound Ca2+ may regulate neuronal activity and should receive more attention in the future.
Genome-Wide Identiﬁcation and Analysis of WRKY Gene Family in Melastoma dodecandrum

: WRKY is one of the largest transcription factor families in plants and plays an important role in plant growth and development as well as in abiotic and biological stresses. However, there is little information about the WRKY family in Melastoma dodecandrum . In this study, 126 WRKY members were identiﬁed in M. dodecandrum . According to phylogenetic analysis, they were divided into three major groups, and group II was further divided into ﬁve subgroups. MedWRKY genes were unevenly distributed on 12 chromosomes. Additionally, the gene structure and sequence composition were similar within the same group and differed between groups, suggesting their functional diversity. The promoter sequence analysis identiﬁed a number of cis-acting elements related to plant growth and development, stress response, and secondary metabolite synthesis in the WRKY gene family. The collinearity analysis showed that gene replication events were the main driving force of MedWRKY gene evolution. The transcriptome data and RT-qPCR analysis suggested that MedWRKY genes had higher expression in the roots and ripe fruit of M. dodecandrum . In short, this paper lays a foundation for further study of the functions and molecular mechanism of M. dodecandrum WRKY gene family.
Antioxidant and Anti-Inﬂammatory Activities of Phenolic Acid-Rich Extract from Hairy Roots of Dracocephalum moldavica

: This study evaluates the antioxidant properties and anti-inﬂammatory potential of polyphe-nolic acid-rich fractions of 80% methanolic extract from the hairy roots of Dracocephalum moldavica . The fractionation of the crude extract yielded the following: a diethyl ether fraction rich in caffeic acid (DM1) (25.85 mg/g DWE), an n-butyl fraction rich in rosmarinic acid (DM3) (43.94 mg/g DWE) and a water residue rich in salvianolic acid B (DM4) (51.46 mg/g DWE). The content of these compounds was determined using high-performance liquid chromatography (HPLC). Their antioxidant activity was evaluated based on DPPH (2,2-diphenyl-1-picrylhydrazyl), ABTS (2,2 (cid:48) -azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) diammonium salt) and FRAP assays. The anti-inﬂammatory activity of the fractions was determined by their effect on nuclear factor kappa-B (NF-κ B) activation and interleukin-1 β (IL-1 β ) production in LPS E. coli stimulated monocytes. The level of pro-inﬂammatory IL-1 β in cells was measured using ELISA. The activation of NF-κ B in THP1-Blue™ cells, resulting in the secretion of SEAP (secreted embryonic alkaline phosphatase), was detected spectrophotometrically using Quanti-Blue reagent. Among the tested fractions, the diethyl ether fraction (DM1) showed the highest antioxidant potential, with an EC 50 value of 15.41 µ g/mL in the DPPH assay and 11.47 µ g/mL in ABTS and a reduction potential of 10.9 mM Fe(II)/g DWE in FRAP. DM1 at a concentration of 10 mg/mL also efﬁciently reduced LPS-induced SEAP secretion (53% inhibition) and IL-1 β production (47% inhibition) without affecting the normal growth of L929 ﬁbroblast cells.
Detection Probability of Gyrfalcons and other Cliff-Nesting Raptors During Aerial Surveys in Alaska.

Gyrfalcons (Falco rusticolus) and other cliffnesting raptors as the Arctic climate changes often requires aerial surveys of their breeding habitats. Because traditional, count-based surveys that do not adjust for differing detection probabilities can provide faulty inference about population status (Link and Sauer 1998, Thompson 2002), it will be important to incorporate measures of detection probability into survey methods whenever possible.
Extending Rust with Support for Zero Copy Communication

In contrast to hardware-based isolation solutions, language-based systems support crossing of isolation boundaries with an overhead of a function call. Moreover, the strong type system of a safe language provides support for secure communication in the face of complex, semantically-rich interfaces, i.e., support for fault isolation and end-to-end zero-copy communication through isolation of object spaces and controlled ownership on the shared exchange heap. If historically, safety was prohibitive due to overheads of a managed runtime, today, languages like Rust achieve the performance of unsafe C hence empowering language-based systems to support practical isolation with fine-grained boundaries and frequent communication. Unfortunately, despite providing the core foundation for isolation of object spaces, i.e., support for a special shared heap, Rust still lacks several abstractions required to support zero-copy communication mechanisms. Existing Rust systems restrict zero-copy passing of data to a set of hand-coded types, hence limiting flexibility of changing interfaces between isolated subsystems. Our work extends the Rust compiler with a static analysis pass that reasons about assignments of references on the shared exchange heap and instruments them with the code that correctly reflects ownership updates on cross-subsystem invocations. This allows us to develop an isolation scheme in which a hierarchical data structure can be passed between isolated subsystems with a single ownership update of its root element.
On the relationship between protist metabarcoding and protist metagenome-assembled genomes

The two most commonly used approaches to study the composition of environmental protist communities are marker gene metabarcoding and whole genome analysis through metagenomics. Raw metabarcoding data are usually processed into Operational Taxonomic Units (OTUs) or amplicon sequence variants (ASVs) through clustering or denoising approaches, respectively. Analogous approaches have been developed to assemble metagenomic sequence reads into metagenome-assembled genomes (MAGs). Understanding the correspondence between the data produced by these two approaches can help to integrate information between the datasets and to explain how metabarcoding OTUs and MAGs are related with the underlying biological entities they are hypothesised to represent. Due to the nature of their construction, MAGs do not contain the most commonly used barcoding loci, meaning that sequence homology approaches cannot be used to match OTUs and MAGs. We made an attempt to match V9 metabarcoding OTUs from the 18S rRNA gene (V9 OTUs) and MAGs from the Tara Oceans expedition (2009-2013) based on the correspondence of their relative abundances across the same set of samples. We evaluated the performance of several methods for detecting correspondence between features in these two compositional datasets and developed a series of controls to filter artefacts of data structure and processing. After selecting the best-performing correspondence metrics, ranking the V9 OTU/MAG matches by their proportionality/correlation coefficients and applying a set of selection criteria, we identified candidate matches between V9 OTUs and MAGs. In a subset of cases, V9 OTUs and MAGs could be successfully matched with one another with a one-to-one correspondence, implying that they likely represent the same underlying biological entity. More generally, matches we observed could be classified into 4 scenarios: Scenario I - one V9 OTU matches more than one MAG; Scenario II - more than one V9 OTU matches more than one MAG; Scenario III - more than one V9 OTU matches one MAG; Scenario IV - one V9 OTU matches one MAG. These diverse scenarios for V9 OTU-MAG matches illustrate the complex nature of the OTU/MAG relationship. Notably, we found some instances in which different OTU-MAG matches from the same taxonomic group were not classified in the same scenario, with all four scenarios possible even within the same taxonomic group, illustrating that factors beyond taxonomic lineage influence the relationship between OTUs and MAGs. Overall, each scenario produces a different interpretation of V9 OTUs, MAGs and how they compare in terms of the genomic and ecological diversity that they represent.
In vitro reconstitution reveals membrane clustering and double-stranded RNA recruitment by the enteroviral AAA+ ATPase 2C

Enteroviruses are a vast genus of positive-sense RNA viruses that cause diseases ranging from common cold to poliomyelitis and viral myocarditis. They encode a membrane-bound AAA+ ATPase, 2C, that has been suggested to serve several roles in virus replication, e.g. as an RNA helicase and capsid assembly factor. As an oligomeric peripheral membrane protein, the low solubility of 2C has hitherto impaired biochemical studies of the full-length protein. Here, we report a biochemical reconstitution poliovirus 2C association with membranes. We show that a conserved glycine divides the N-terminal membrane-binding domain of 2C into two amphipathic helix regions, AH1 and AH2. AH2 is the main mediator of 2C oligomerization, and is sufficient for its membrane binding. AH1 is the main mediator of a novel function of 2C: clustering of membranes. Cryo-electron tomography reveal that several 2C copies mediate this function by localizing to vesicle-vesicle interfaces. 2C- mediated clustering is partially outcompeted by nucleic acids, suggesting a way by which 2C can switch from an early role in coalescing replication organelles, and recruiting lipid droplets to them, to a later role where 2C assists RNA replication and particle assembly. 2C is sufficient to recruit RNA to membranes, with a preference for double-stranded RNA, thus being a candidate for the factor that localizes viral RNA replication to membranes. Finally, the in vitro reconstitution revealed that full- length 2C localized to a membrane has weak RNA chaperoning activity, dependent on having a free N terminus, but does not possess ATP-dependent helicase activity. Together, this study suggests two novel roles for 2C in membrane clustering and double-stranded RNA recruitment to membranes, and calls into question a role of 2C as an RNA helicase. The reconstitution of functional, 2C-decorated vesicles provides a platform for further experimental studies into this protein and its roles in enterovirus replication.
The Role of PKR on Modulating Neuroinflammation and Cognitive Dysfunctions in a Peripheral Inflammation Model

Background Increasing lines of evidence have shown that systemic inflammation may contribute to neuroinflammation and accelerate the progression of neurodegenerative diseases. The double-stranded RNA-dependent protein kinase (PKR) is a key signaling molecule that regulates immune responses by regulating macrophage activation, various inflammatory pathways, and the formation of inflammasomes. This study aims to study the role of PKR in regulating systemic inflammation-triggered neuroinflammation and cognitive dysfunctions. Methods In this three-part study, laparotomy was used as an experimental model to study neuroimmune responses triggered by systemic inflammation. In the first part, wild-type C57BL/6J and C57BL/6-Tg(CD68-EGFP)1Drg/J mice were randomly assigned to laparotomy under sevoflurane anesthesia or sevoflurane anesthesia alone as a control. The effects of systemic inflammation on neuroinflammation and cognitive function were examined. In the second part, PKR-/- mice were used to determine the role of PKR in regulating laparotomy-induced systemic inflammation, neuroinflammation and cognitive dysfunctions. For the third part, rAAV-DIO-PKR-K296R was injected intracerebroventricularly into the right lateral ventricle of ChAT-IRES-Cre-eGFP mice to inhibit PKR activation in cholinergic neurons. The effects of blocking PKR in cholinergic neurons on modulating glucose metabolism and cognition in the laparotomy model were examined. Results Genetic deletion of PKR in mice potently ameliorated the laparotomy-induced peripheral and neural inflammatory responses (downregulated pro-inflammatory cytokine expressions and activation of microglia), and cognitive dysfunctions. Inhibition of PKR in cholinergic neurons in mice could rescue the laparotomy-induced brain glucose hypometabolism and cognitive deficits. Conclusions Our results suggested the critical role of PKR on modulating neuroinflammation and cognitive dysfunctions in a peripheral inflammation model. PKR could be a pharmacological target for treating systemic inflammation-induced neuroinflammation and cognitive deficits.
Signal-Injection-Assisted Full-Order Observer With Parameter Adaptation for Synchronous Reluctance Motor Drives

A back-electromotive-force-based position observer for motion-sensorless synchronous reluctance motor (SyRM) drives is augmented with parameter adaptation laws for improved operation at all speeds, including standstill. The augmented observer is theoretically analyzed under various operating conditions. The analysis indicates that the stator-resistance adaptation should be enabled only at low speeds, the d-axis inductance adaptation should be enabled only at medium and high speeds near no load, and the q-axis inductance adaptation should be enabled only at high speeds under high load. The augmented observer is experimentally evaluated using a 6.7-kW SyRM drive.
Equilibrium Labor Market Search and Health Insurance Reform, Third Version

We present and empirically implement an equilibrium labor market search model where risk averse workers facing medical expenditure shocks are matched with ﬁrms making health insurance coverage decisions. Our model delivers a rich set of predictions that can account for a wide variety of phenomenon observed in the data including the correlations among ﬁrm sizes, wages, employer-sponsored health insurance oﬀering rates, turnover rates and workers’ health compositions. We estimate our model by Generalized Method of Moments using a combination of micro datasets including the Survey of Income and Program Participation, the Medical Expenditure Panel Survey and the Kaiser Family Employer Health Insurance Beneﬁts Survey. We use our estimated model to evaluate the equilibrium impact of the 2010 Aﬀordable Care Act (ACA) and compare it with other health care reform proposals. We also use the estimates of the early impact of the ACA as a model validation. We ﬁnd that the full implementation of the ACA would reduce the uninsured rate among the workers in our estimation sample from about 21.3% in the pre-ACA benchmark economy to 6.6%. We also ﬁnd that income-based premium subsidies for health insurance purchases from the exchange play an important role for the sustainability of the ACA; without the premium subsidies, the uninsured rate would be around 15.8%. In contrast, as long as premium subsidies and health insurance exchanges with community ratings stay intact, ACA without the individual mandate, or without the employer mandate, or without both mandates, could still succeed in reducing the uninsured rates to 11.4%, 7.5% and 12.9% respectively. Previous versions of this paper can be found at: <a href="url">http://ssrn.com/abstract=2199551</a> <a href="url">http://ssrn.com/abstract=2625669</a>
Market segmentation and the impact of online media

Segmentation in the pharmaceutical industry is blurred by the complicated market dynamics of the industry: even the classic definition of the customer is not relevant. The customer base is made up of a number of stakeholders, which includes the patient and caregiver. These patients and caregivers have become more empowered and are using the internet as their primary source of information. The internet is developing at an astonishing rate and even healthcare professionals have embraced it. Legislative restrictions make it difficult for marketers to communicate directly with patients, so new strategies need to be developed. This paper looks at the impact of online media on market segmentation within the pharmaceutical industry, and provides practical solutions on how to tackle the dilemma.
Approaches to water springs in literature: a systematic bibliographic review

: The protection, conservation, evaluation, and monitoring of natural water sources are the basis for Integrated Water Resources Management and Planning, including spring water sources which have special importance for the ecosystem services provided. The definition of spring water in scientific literature is characterized by imprecision and subjective interpretations. The term "spring" is included in the Brazilian environmental legislation. It needs to be structured by involving the different areas of knowledge that study them since the applicability of legal penalties established in environmental laws depends on its correct understanding. This research aimed to identify and analyze the information available in academic-scientific literature, as well as in non-scientific materials or documents related to spring water, for characterizing the main approaches currently applied to this topic. The methodology was based on a Systematic Literature Review (SLR) developed through three stages: 1. SLR planning; 2. research processing; and 3. expected results. These steps frame the Input-Processing-Output system, which is intended to guarantee the consistency of the data collected with the review's objectives to identify, describe, and analyze the scientific literature on the subject in a simplified and organized way. The articles and documents consulted were filtered and classified according to their relevance and relationship with the topic. Also, it formulated some categories to group all the references according to the main approaches. 1.216 articles and 960 materials/documents were checked, and 102 references were finally chosen. It was identified that the physical-chemical and microbiological monitoring and assessment of surface water quality had the highest number of associated results, showing an academic priority in seeking ways to ensure human water supply, disregarding all ecological and environmental functions that spring water has.