Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Placental Extracellular Vesicles-Associated Fas Ligand and TNF-Related Apoptosis-Inducing Ligand in Pregnancies Complicated by Early and Late Onset Preeclampsia

Preeclampsia (PE) is a hypertensive disorder that affects 2–8% of pregnancies and is one of the main causes of fetal, neonatal, and maternal mortality and morbidity worldwide. Although PE etiology and pathophysiology remain unknown, there is evidence that the hyperactivation of maternal immunity cells against placental cells triggers trophoblast cell apoptosis and death. It has also been reported that placenta-derived extracellular vesicles (EV) carry Fas ligand (FasL) and Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and trigger apoptosis in Jurkat T cells. This study aimed to quantify and compare FasL and TRAIL expression in EV derived from cultures of placenta explants from women with PE (early versus late) and women with uncomplicated pregnancies. Also, the study assessed EV capacity to induce apoptosis in Jurkat T cells. The authors isolated EV from placenta explant cultures, quantified FasL and TRAIL using ELISA, and analyzed EV apoptosis-inducing capability by flow cytometry. Results showed increased FasL and TRAIL in EV derived from placenta of women with PE, and increased EV apoptosis-inducing capability in Jurkat T cells. These results offer supporting evidence that EV FasL and TRAIL play a role in the pathophysiology of PE.
The Role of Herpes Viruses in Pulmonary Fibrosis

Pulmonary fibrosis (PF) is a serious lung disease which can result from known genetic or environmental exposures but is more commonly idiopathic (IPF). In familial PF (FPF), the majority of identified causal genes play key roles in the maintenance of telomeres, the protective end structures of chromosomes. Recent evidence suggests that short telomeres may also be implicated causally in a significant proportion of idiopathic cases. The possible involvement of herpes viruses in PF disease incidence and progression has been examined for many years, with some studies showing strong, statistically significant associations and others reporting no involvement. Evidence is thus polarized and remains inconclusive. Here we review the reported involvement of herpes viruses in PF in both animals and humans and present a summary of the evidence to date. We also present several possible mechanisms of action of the different herpes viruses in PF pathogenesis, including potential contributions to telomere attrition and cellular senescence. Evidence for antiviral treatment in PF is very limited but suggests a potential benefit. Further work is required to definitely answer the question of whether herpes viruses impact PF disease onset and progression and to enable the possible use of targeted antiviral treatments to improve clinical outcomes.
MRI-Based Geometric Modeling for Personalized Transcranial Magnetic Stimulation in Age-Related Neurodegenerative Diseases

Structural magnetic resonance imaging (MRI) provides a powerful and financially favorable imaging modality, with the additional benefits of its high spatial resolution and plausible multiscale measurements of brain morphometry (Madan and Kensinger, 2016; Lu, 2020). With the use of MRI-based morphometry, region-specific cortical features have been found to enhance the accuracy of diagnosis, and even predict the treatment responses (Bartlett et al., 2018). Of all the advanced modalities of non-invasive brain stimulation (NIBS), transcranial magnetic stimulation (TMS) is an FDA-cleared technique for the treatments of the main types of brain disorders through non-invasive modulation of brain activities using a magnetically induced electric field (E-field) (Rossi et al., 2009). Although using individualMRI images to guide TMS has improved the accuracy of localizing the stimulation targets, the treatment response still greatly varies between individuals, particularly in the patients with age-related neurodegenerative diseases (Polanía et al., 2018). Among the factors that determine the variability of TMS-induced effects, stimulation intensity and individual cortical morphometry were highlighted as brain stimulation-specific factors (Polanía et al., 2018).
Antifungal activities of the extracts from Curcuma phaeocaulis against Phoma wasabiae

The bioactivity of water and 95% ethanol extracts from C. phaeocaulis against P. wasabiae Yokogi were tested in the laboratory with growth rate method. Results showed that the inhibition rate of 95% ethanol extracts from C. phaeocaulis was 67.08% on P. wasabiae Yokogi at the concentration of 1.0×10-3 g/mL. Then the 95% ethanol extracts of C.phaeocaulis were extracted by Hexane, Ethylacetate and methanol step by step and the antifungal activity were tested further. The results indicated that active components were present in Hexane extracts of C. phaeocaulis and it had 79.9% inhibiting rate on P. wasabiae Yokogi at the concentration of 1.0×10-3 g/mL with EC50 being 0.3299×10-3 g/mL, and 97.2% inhibiting rate on spore germination against P.wasabiae Yokogi at the concentration of 10.0×10-3 g/mL. Three representative fungi as tested objects for further bioactivity study. The EC50 of extracts with Hexane to Fusarium graminearum, Sclerotinia sclerotiorum, Botrytis Cirerea, were 0.2517×10-3 g/mL, 0.2809×10-3 g/mL, 0.1749×10-3 g/mL, respectively.
AKTIVITAS ANTIOKSIDAN DAN ANTIBAKTERI EKSTRAK POLAR DAN NON POLAR BIJI SELASIH (Ocimum sanctum Linn) [Antioxidant and Antibacterial Activities from Polar and Non Polar Basil (Ocimum sanctum Linn) Seed Extracts]

The aims of this study were to determine total phenolic content, antioxidant activity and antibacterial activity of polar and nonpolar extracts of basil (O. sanctum L. ) seed. Seeds of basil (O. sanctum L. ) were extracted using a soxhlet extractor using four types organic solvent, i.e. chloroform, ethyl acetate, acetone, and methanol for eight hours each. The total phenolic content was determined using Folin Ciocalteu method, antioxidant activity was determined using reducing power and DPPH (1,1-diphenyl,2-picrylhydrazyl) scavenging activity methods, while antibacterial activity was tested using agar diffusion method. The result showed that the highest total phenolic content and antioxidant activity was obtained in methanol extract with 3.63 ± 0.21 mgGAE/g phenolic total, 58.39 ± 3.81 m ek/g using reducing power method and 85.73 ± 0.86% free radical scavenging activity. Furthermore the result of antibacterial activity testing showed that the highest diameter of inhibition zone was observed in ethyl acetate extract inhibition on E.coli, P.aeruginosa, B.subtilis, and S.aureus where its inhibition zone were 13.53 ± 0.63; 10.67 ± 1.05; 14.93 ± 0.80, and 13.46 ± 0.79 mm, respectively. This result suggests that both polar and nonpolar basil seed extracts possess specific biological activity. This data provide valuable and strong database for exploration of natural antibacterial agents and antioxidant for food and health industry application.
Impact and Challenges of Integrating Artificial Intelligence and Telemedicine into Clinical Ophthalmology

Supplemental Digital Content is available in the text Abstract Aging populations and worsening burden of chronic, treatable disease is increasingly creating a global shortfall in ophthalmic care provision. Remote and automated systems carry the promise to expand the scale and potential of health care interventions, and reduce strain on health care services through safe, personalized, efficient, and cost-effective services. However, significant challenges remain. Forward planning in service design is paramount to safeguard patient safety, trust in digital services, data privacy, medico-legal implications, and digital exclusion. We explore the impact and challenges facing patients and clinicians in integrating AI and telemedicine into ophthalmic care—and how these may influence its direction.
Amyloid and tau positive mild cognitive impairment: clinical and biomarker characteristics of dementia progression

Supplemental Digital Content is available in the text Abstract Background: According to the amyloid, tau, neurodegeneration research framework classification, amyloid and tau positive (A+T+) mild cognitive impairment (MCI) individuals are defined as prodromal Alzheimer disease. This study was designed to compare the clinical and biomarker features between A+T+MCI individuals who progressed to progressive MCI (pMCI) and those who remained stable MCI (sMCI), and to identify relevant baseline clinical biomarker and features that could be used to predict progression to dementia within 2 years. Methods: We stratified 197 A+T+MCI individuals into pMCI (n = 64) and sMCI (n = 133) over 2 years. Demographics and cognitive assessment scores, cerebrospinal fluid (CSF), and neuroimaging biomarkers (18F-florbetapir positron emission tomography mean standardized uptake value ratios [SUVR] and structural magnetic resonance imaging [MRI]) were compared between pMCI and sMCI at baseline, 12- and 24-month follow-up. Logistic regression models then were used to evaluate clinical baseline and biomarker features that predicted dementia progression in A+T+MCI. Results: pMCI individuals had higher mean 18F-florbetapir SUVR, CSF total-tau (t-tau), and p-tau181P than those in sMCI individuals. pMCI individuals performed poorer in cognitive assessments, both global and domain specific (memory, executive, language, attention, and visuospatial skills) than sMCI. At baseline, there were significant differences in regions of interest of structural MRI between the two groups, including bilateral amygdala, hippocampus and entorhinal, bilateral inferior lateral ventricle, left superior and middle temporal, left posterior and caudal anterior cingulate (P < 0.05). Baseline CSF t-tau levels and cognitive scores of Montreal cognitive assessment, functional assessment questionnaire, and everyday cognition by the patient's study partner language domain could predict progression to dementia in A+T+MCI within 2 years. Conclusions: In future clinical trials, specific CSF and cognitive measures that predict dementia progression in A+T+MCI might be useful risk factors for assessing the risk of dementia progression.
Analysis of Puerarin and Daidzein in Gegen Qinlian Preparations by High Performance Capillary Electrophoresis

Objective: To analyze isoflavones and determine the content of puerarin and daidzein in Gegen Qinlian preparations by high performance capillary electrophoresis(HPCE). Methods:555. 8μg·mL-1 2 - (4 - Hydroxy-phenyl)ethylammonium chloride was used as an internal standard,a buffer was composed of 85% 30 mmol· L-1 borax(pH =9. 2)and 15% methanol. CE was performed using a 52 cm(30 cm to detector) ×50μm fused - silica capillary tube. Separation voltage was 18 kV,sampling pressure was 6. 7 kPa,sampling time was 1 s and the temperature was maintained at 30 ℃. Results: The selected components were successfully separated within 8 min, the recoveries of puerarin and daidzein were 99. 75% and 98. 59% respectively;RSD were 2. 0% and 1. 6% respectively. Conclusion; This method can be used for the determination of puerarin and daidzein in prescriptions contained Radix Puerariae with good precision and recoveries.
Development and application of a new low cost electronic nose for the ripeness monitoring of banana using computational techniques (PCA, LDA, SIMCA, and SVM)

Potential application of a metal oxide semiconductor based electronic nose (e-nose) as a non-destructive instrument for monitoring the change in volatile production of banana during the ripening process was studied. The proposed e-nose does not need any advanced or expensive laboratory equipment and proved to be reliable in recording meaningful differences between ripening stages. Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Soft Independent Modelling of Class Analogy (SIMCA) and Support Vector Machines (SVM) techniques were used for this purpose. Results showed that the proposed e-nose can distinguish between different ripening stages. The e-nose was able to detect a clear difference in the aroma fingerprint of banana when using SVM analysis compared with PCA and LDA, SIMCA analysis. Using SVM analysis, it was possible to differentiate and to classify the different banana ripening stages, and this method was able to classify 98.66% of the total samples in each respective group. Sensor array capabilities in the classification of ripening stages using loading analysis and SVM and SIMCA were also investigated, which leads to develop the application of a specific e-nose system by applying the most effective sensors or ignoring the redundant sensors.
Privacy-Preserving Task Matching With Threshold Similarity Search via Vehicular Crowdsourcing

In vehicular crowdsourcing, task requesters rely on a server to distribute spatial crowdsourcing tasks to on-road vehicular workers based on interests and locations. To protect the privacy of the interests and locations, both requesters and workers prefer to encrypt the information before uploading them to the server. However, such an encryption-before-outsourcing paradigm makes it a challenging issue to conduct the task matching. In this paper, we propose a Privacy-Preserving Task Matching (PPTM) with threshold similarity search via vehicular crowdsourcing. We first propose an interest-based PPTM by transforming vehicular workers’ interests into binary vectors. By using Symmetric-key Threshold Predicate Encryption (STPE) and proxy re-encryption, PPTM achieves privacy-preserving multi-keyword task matching with Jaccard similarity search in multi-worker multi-requester setting. Furthermore, by comparing the Euclidean distances between workers and requesters against a pre-defined threshold, PPTM preserves the location privacy of workers and requesters that only reveals the comparison results to the crowdsourcing server. The security analysis and extensive experiments demonstrate that PPTM protects the confidentiality of locations and interests of requesters and workers while achieving the efficient task matching.
Sum Rate Analysis of Generalized Space Shift Keying-Aided MIMO-NOMA Systems

We investigate the sum rate performance of a generalized space shift keying (GSSK)-aided, non-orthogonal multiple access (NOMA) network. In particular, we consider a multiple-input multiple-output (MIMO) NOMA downlink channel, where the base station employs GSSK modulation to transmit additional information to the NOMA users. We present a novel energy-based maximum likelihood (ML) detection strategy at the NOMA users to decode the active antenna indices. We derive a closed-form expression for the average pairwise error probability of the energy-based ML strategy to find a union bound on the bit error probability. Further, we derive the expression for the overall sum rate of the proposed GSSK-aided MIMO-NOMA system. Through numerical evaluations, we show that the proposed system outperforms the conventional MIMO-NOMA system, in terms of spectral efficiency.
Robust and Accurate RGB-D Reconstruction With Line Feature Constraints

Scene reconstruction with consumer-level RGB-D cameras has developed considerable momentum in both robotics and vision communities. In the literature of robotics, high-quality camera tracking, the key to accurate reconstruction, is challenging in geometric featureless scenes or under large lighting variation. In this letter, we propose an accurate RGB-D reconstruction approach, by incorporating 3D line features into key steps of the pipeline to significantly improve tracking robustness and reduce error accumulation. Our reconstruction approach is characterized by three key designs. First, we propose a robust 3D line extractor to efficiently extract accurate and consistent 3D lines from RGB-D data. Moreover, we design a joint objective for frame-to-model scan alignment considering both dense points and 3D lines in a robust error metric. With extra constraints from 3D lines and the robust error metric, scan alignment is further enhanced in challenging situations even without any heuristics for spurious correspondence pruning. Finally, we propose an efficient submap-based hierarchical optimization considering both point and 3D line correspondences to significantly reduce the accumulated error in camera tracking and obtain an accurate global 3D model. Extensive experiments on synthetic and real-world datasets demonstrate that our method outperforms state-of-the-art RGB-D reconstruction approaches for common indoor or outdoor scenes in challenging situations of practical scanning.
Multi-View Feature Construction Using Genetic Programming for Rolling Bearing Fault Diagnosis [Application Notes]

Rolling bearing fault diagnosis is an important task in mechanical engineering. Existing methods have several limitations, such as requiring domain knowledge and a large number of training samples. To address these limitations, this paper proposes a new diagnosis approach, i.e., multiview feature construction based on genetic programming with the idea of ensemble learning (MFCGPE), to automatically construct high-level features from multiple views and build an effective ensemble for identifying different fault types using a small number of training samples. The MFCGPE approach uses a new program structure to automatically construct a flexible number of features from every single view. A new fitness function based on accuracy and distance is developed in MFCGPE to improve the discriminability of the constructed features. To further improve the generalization performance, an ensemble of classifiers based on k-nearest neighbor is created by using the constructed features from every single view. Three bearing datasets and 19 competitive methods are used to validate the effectiveness of the new approach. The results show that MFCGPE achieves higher diagnostic accuracy than all the compared methods on the three datasets with a small number of training samples.
A Novel Nested Array for Real-Valued Sources Exploiting Array Motion

In this letter, a novel nested array is proposed which not only increases the degrees of freedom (DOF) but also reduces the mutual coupling that occurs in the general nested array structure by moving the original array only half wavelength. Here we deal with real-valued sources like AM or BPSK whereby we can explore the property of the sum coarray along with the difference coarray of the synthetic array (SA). It is assumed that the sensing environment does not change over the array motion of half wavelength. First, we develop the novel nested array and prove that the sum difference coarray (SDCA) of SA is hole-free up to a certain number. Then we provide closed-form expressions for the number of unique and consecutive lags of the SDCA of SA. We also optimize the array for a given number of sensors. Simulation results show the superiority of the proposed array over other existing arrays.
UNAME Tool: Automatic Generation of Computer Resources Monitoring Scripts

Decision-making regarding performance issues re- quires computer systems monitoring at any level of service provisioning. However, most of the available tools do not always allow flexibility, or when it does, it impacts directly the resource consumption through an intrusive methodology. This paper presents the UNAME tool, which proposes the automatic generation of Shell scripts for monitoring computational resources. Through a GUI, the user can drag in or out the components to be evaluated. The Linux monitoring commands were mapped to high-level representations of the computational resources, and now the user, through little interaction or knowledge about scripting, can generate their own scripts to monitor the required system resources. To demonstrate the UNAME tool feasibility we provide a case study and an evaluation scenario. The results demonstrated the effectiveness of the proposed tool.
Chemical and Biological Applications Based on Plasmonic Optical Fiber Sensors

The use of optical fibers has evolved from an optical transmission waveguide to a more intricated device for bio-chemical sensing. The possibility of measuring target substances with rapid and low-cost tools is still a main challenge in different application fields, from environmental monitoring to the medical-diagnostic sector. In recent decades, plasmonic fiber-optic sensors have gained great interest due to their excellent sensitivity and compactness, allowing the possibility of remote sensing for different target analytes that is real-time and label-free. Such sensors have constantly evolved over time. In this work, a short overview on plasmonic optical fiber sensors is presented, including illustrations that focus on the applications and achievements so far.
Communication-Aware Multi-Agent Metareasoning for Decentralized Task Allocation

Metareasoning refers to reasoning about one’s own decision making process. This paper considers metareasoning about the decision making process in multi-agent settings. We present a multi-agent metareasoning approach that enables a multi-agent team to select which task allocation algorithm to use as a function of changing communication quality level. Given a set of multi-agent task allocation algorithms, we synthesize a policy that prescribes the best algorithm to use among a predefined set of algorithms for a given communication level. Since each agent in the team runs the same policy, the team (or a part of the team) will collectively switch between task allocation algorithms as a function of the observed level of communication. We apply reactive synthesis to generate the policy from high-level specifications written in Linear Temporal Logic encoding the agents’ switching behavior with respect to the state of the environment. We perform experiments in simulation to identify the best performing algorithms under different communication levels. The communication environment is modeled using the Rayleigh fading model and communication estimation is done through the exchange of heartbeat messages among agents. We test our metareasoning policy in three types of scenarios: search & rescue, fire monitoring, and ship protection scenarios. For each scenario, we demonstrate that our policy achieved better performance with respect to either max distance traveled, max number of transmitted messages or both compared to running any single algorithm.
Equivalent Dipoles for the Prediction of IC Noise Coupling

Generally, when near-field amplitude and phase of an unknown IC are measured, its equivalent dipole array can be determined by solving the corresponding linear equations. However, we often use the phase-free near-field scanning in engineering applications. Due to the lack of phase information, the corresponding equations become nonlinear, and it is more difficult to solve them. Fortunately, differential evolution (DE), a kind of global optimization algorithm, can handle such nonlinear equations effectively. In this paper, we verify the effectiveness of DE algorithm in equivalent dipole reconstruction by a numerical and a measurement example. Both examples show the good performance of DE algorithm in predicting noise coupling.
Electroconductivity of Tetraethylammonium Tetrafluoroborate in Propylene Carbonate at Various Temperatures

Electrical conductivities of tetraethylammonium tetrafluoroborate in propylene carbonate were measured over wide ranges of salt concentration and temperature. The data have been interpreted in terms of ion–solvent and ion–ion interactions using the Lee–Wheaton equation at low concentrations and the semiempirical Castell–Amis equation at high concentrations. The association constants, KA, and limiting molar conductivities at infinite dilution, Λ0, have been calculated at (283.15, 291.15, 298.15, and 313.15) K. The results indicate that Et4NBF4 is almost unassociated in this solvent medium. The evaluation of Stokes radii, rS, of the ions at 298.15 K indicates that Et4N+ and BF4– remain scarcely solvated in the propylene carbonate. The specific conductivity, χ, of Et4NBF4 in propylene carbonate was determined in a concentration range of (0.15 to 1.4) mol·kg–1 at (253.15, 273.15, 293.15, 313.15, and 333.15) K and was interpreted by the transition state theory. The activation energies for conductivity and for .