Miracle-dz/UniFAR-FTUs huggingface dataset:
Virally Suppressed People Living with HIV Who Use Opioids Have Diminished Latency Reversal

Of the 12 million people who inject drugs worldwide, 13% live with HIV. Whether opioid use impacts HIV pathogenesis and latency is an outstanding question. To gain insight into whether opioid use influences the proviral landscape and latent HIV reservoir, we performed intact proviral DNA assays (IPDA) on peripheral blood mononuclear cells (PBMCs) from antiretroviral therapy (ART)-suppressed people living with HIV (PWH) with or without current opioid use. No differences were observed between PWH with and without opioid use in the frequency of HIV intact and defective proviral genomes. To evaluate the latent reservoir, we activated PBMCs from ART-suppressed PWH with or without opioid use and assessed the induction of HIV RNA. PWH using opioids had diminished responses to ex vivo HIV reactivation, suggesting a smaller reversible reservoir of HIV-1 latently infected cells. However, in vitro studies using primary CD4+ T cells treated with morphine showed no effect of opioids on HIV-1 infection, replication or latency establishment. The discrepancy in our results from in vitro and clinical samples suggests that while opioids may not directly impact HIV replication, latency and reactivation in CD4+ T cells, opioid use may indirectly shape the HIV reservoir in vivo by modulating general immune functions.
The Dark Halo – Spheroid Conspiracy Reloaded: Evolution with Redshift

Abstract The total density profiles of elliptical galaxies can be fit by a single power law, i.e., ρtot ∝ rγ with γ ≈ −2. While strong lensing observations show a tendency for the slopes to become flatter with increasing redshift, simulations indicate an opposite trend. To understand this discrepancy, we study a set of simulated spheroids formed within the cosmological framework. From our simulations we find that the steepness of the total density slope correlates with the compactness of the stellar component within the half-mass radius, and that spheroidal galaxies tend to be more compact at high redshifts than their present-day counterparts. While both these results are in agreement with observations, the observed trend of the total density slope with redshift remains in contradiction to the results from simulations.
UNDERLYING PHYSICS OF THE THERMOCHEMICAL E MODEL IN DESCRIBING LOW-FIELD TIME-DEPENDENT DIELECTRIC BREAKDOWN IN SIO2 THIN FILMS

The underlying physics behind the success of the thermochemical E model in describing time-dependent dielectric breakdown (TDDB) in SiO2 thin films is presented. Weak bonding states can be broken by thermal means due to the strong dipolar coupling of intrinsic defect states with the local electric field in the dielectric. This dipole-field coupling serves to lower the activation energy required for thermal bond-breakage and accelerates the dielectric degradation process. A temperature-independent field acceleration parameter γ and a field-independent activation energy ΔH can result when different types of disturbed bonding states are mixed during TDDB testing of SiO2 thin films. While γ for each defect type alone has the expected 1/T dependence and ΔH shows a linear decrease with electric field, a nearly temperature-independent γ and a field-independent ΔH can result when two or more types of disturbed bonding states are mixed. The good agreement between long-term TDDB data and the thermochemical model su.
Defining a Social Role for Ports: Managers’ Perspectives on Whats and Whys

It is undoubtedly true that ports can modify aspects of the regions where they are inserted in many different ways. Scholars have presented various perspectives on the influence of ports in society, including their roles according to their purpose. Surprisingly, in the age of sustainable development, the social roles of ports have not been explored in depth, and this offers an opportunity to increase the knowledge of this sector. This paper aims to investigate how managers in ports perceive their roles in the social dimension and why they think they should exist, presenting opportunities to align business objectives with the expectations of other stakeholders. Applying the content analysis technique, 28 interviews were conducted with managers in Brazilian ports and themes were developed to represent their views on social roles (5) and the reasons for adopting them (6). Overall, managers perceive social roles as part of the strategic business plan and present reasons to adopt them, ranging from compulsory to voluntary. Conclusions suggest that more needs to be done to expand the understanding of a pragmatic approach to social roles and to develop more focused actions according to the reasons for adopting social roles.
Magnetic control of electric-field domains in semiconductor superlattices

1IBM Research Division, T. J. Watson Research Center, Yorktown Heights, New York 10598 2Max-Planck-Institut für Festkörperforschung, Heisenbergstrasse 1, 70569 Stuttgart, Germany 3Grenoble High Magnetic Field Laboratory, Max-Planck-Institut für Festkörperforschung and CNRS, BP 1 38042 Grenoble, France 4Institut für Festkörperphysik, Universität Hannover, Appelstrasse 2, 30167 Hannover, Germany (Received 8 April 1998 )
The Efficacy of Mortgage Lending on Geographically Disparate and Differently Priced Residential Neighborhoods in Shanghai

As both a vibrant industry and necessity for people’s lives, housing has attracted much attention in recent years. This article examines the efficacy of both loosening and tightening policies on mortgage lending in different priced housing markets in Shanghai, China, from 2014 to 2018 using daily average sale prices across 1,824 neighborhoods, with price-classified cluster analysis and policy-informed hedonic regressions. The results show that (1) the effects of mortgage lending policy interventions varied significantly and the overall spatial distribution gravitated toward subway networks and varied throughout the years; (2) the effects of interventions were time lagged but varied by different priced neighborhoods; and (3) although the accumulated number of both loosening and tightening policies were both significant, only the effects of tightening policies were significant overall. This article contributes to the existing literature by combining the spatial-temporal component in policy studies, providing detailed mortgage lending policy intervention variables, and expanding the scope of study from housing prices to housing transaction frequencies.
Thickness Determination of Ultrathin 2D Materials Empowered by Machine Learning Algorithms

The number of layers of 2D materials is of great significance for regulating the performance of nanoelectronic devices and optoelectronic devices, where the optimal thickness of the target sample should be determined before further physical research or device manufacturing steps. At present, a variety of different optical technologies have been proposed to determine the thickness of samples by using the relationship between the number of layers and optical properties, including optical contrast, optical imaging, Raman spectra, photoluminescence spectra, nonlinear spectra, near‐field optical imaging, ellipsometry spectra, and hyperspectral imaging. In the past decade, the rapidly growing number of 2D materials and their heterostructures has exceeded the capacity of traditional experimental and computational methods. In recent years, machine learning (ML) is emerging as a powerful tool to support such traditional methods, which brings new opportunities to tap the potential of optical technology in a more perspicacious way. The application of optical technology has greatly facilitated the acquisition of optical information of materials, while ML algorithms provide a fast, high‐throughput, and intelligent way to complete back‐end data processing and inference. A profound integration of conventional optical technologies and ML algorithms significantly helps 2D materials progress in basic studies and practical applications and further promotes industrial manufacturing.
Predicting synthetic lethal interactions using conserved patterns in protein interaction networks

In response to a need for improved treatments, a number of promising novel targeted cancer therapies are being developed that exploit human synthetic lethal interactions. This is facilitating personalised medicine strategies in cancers where specific tumour suppressors have become inactivated. Mainly due to the constraints of the experimental procedures, relatively few human synthetic lethal interactions have been identified. Here we describe SLant (Synthetic Lethal analysis via Network topology), a computational systems approach to predicting human synthetic lethal interactions that works by identifying and exploiting conserved patterns in protein interaction network topology both within and across species. SLant out-performs previous attempts to classify human SSL interactions and experimental validation of the models predictions suggests it may provide useful guidance for future SSL screenings and ultimately aid targeted cancer therapy development.
Multi-scale modeling of mechanotransduction in the utricle.

We review recent progress in using numerical models to relate utricular hair bundle and otoconial membrane structure to the functional requirements imposed by natural behavior in turtles. Section I reviews the evolution of experimental attempts to understand vestibular system function with emphasis on turtles, including data showing that accelerations occurring during natural head movements achieve higher magnitudes and frequencies than previously assumed. Section 2 reviews quantitative anatomical data documenting topographical variation in the structures underlying macromechanical and micromechanical responses of the turtle utricle to head movement: hair bundles, otoconial membrane (OM), and bundle-OM coupling. Section 3 reviews macromechanical models that incorporate realistic anatomical and mechanical parameters and reveal that the system is significantly underdamped, contrary to previous assumptions. Section 4 reviews work based on micromechanical models, which demonstrates that topographical variation in the structure of hair bundles and OM, and their mode of coupling, results in regional specializations for signaling of low frequency (or static) head position and high frequency head accelerations. We conclude that computational models based on empirical data are especially promising for investigating mechanotransduction in this challenging sensori-motor system.
A MODEL FOR STRATEGIC VOTING

A model combining an individual voter’s personal preferences (a cardinal utility rating) with the preferences of the rest of the electorate (as measured by pre-election polls) is investigated to determine how a voter may maximize his expected satisfaction with the election outcome. The basic model of McKelvey and Ordeshook for a one man-one vote election procedure is generalized to one man-N votes, approval voting and committee elections. Explicit decision conditions are derived for each procedure. An approximation technique is described and some numerical results are included. The final section extends the basic deterministic model to a situation in which the optimal voting strategy may be probabilistic. The model can be used to compare voting procedures as well as the strategies available to a voter under a particular voting procedure.
Deep Learning for Multi-Class Identification From Domestic Violence Online Posts

Domestic violence (DV) is not only a major health and welfare issue but also a violation of human rights. In recent years, domestic violence crisis support (DVCS) groups active on social media have proven indispensable in the support services provided to victims and their families. In the deluge of online-generated content, the significant challenge arises for DVCS groups’ to manually detect the critical situation in a timely manner. For instance, the reports of abuse or urgent financial help solicitation are typically obscured by a vast amount of awareness campaigns or prayers for the victims. The state-of-the-art deep learning models with the embeddings approach have already demonstrated superior results in online text classification tasks. The automatic content categorization would address the scalability issue and allow the DVCS groups to intervene instantly with the exact support needed. Given the problem identified, the study aims to: 1) construct the novel “gold standard’ dataset from social media with multi-class annotation; 2) perform the extensive experiments with multiple deep learning architectures; 3) train the domain-specific embeddings for performance improvement and knowledge discovery; and 4) produce the visualizations to facilitate models analysis and results in interpretation. The empirical evidence on a ground truth dataset has achieved an accuracy of up to 92% in classes prediction. The study validates an application of cutting edge technology to a real-world problem and proves beneficial to DVCS groups, health care practitioners, and most of all victims.
Studies of Transient Photoplasma Evolution in an Electrostatic Field: Single Particle Motion to Its Collective Behavior

Though the plasma is an ensemble of charged particles, its behavior in an electrostatic field is different from that of individual particles. It shows a collective behavior as a result of long-range Coulomb interactions among the charged particles. To elucidate the plasma behavior, the transient evolution of photoplasma in an applied electrostatic field is carried out in two different density regimes where the plasma shows its single particle motion and collective behavior. In the case of low-density plasma, the external electric field dominates the plasma motion. The electrons and ions act as two independent entities and the plasma shows its single particle behavior in the external field, whereas in the high-density plasma regime, the self-generated electric field in the plasma is comparable to the applied external field. The plasma motion is governed by both the internal ambipolar electric field in the plasma as well as the applied electrostatic field. Thus, the plasma shows its collective motion due to Coulomb interactions among the charged particles.
Scene matching localization and orientation algorithm based on STN_Siamese network

Aiming at the problem that the traditional scene matching navigation algorithm needs to manually design features, a scene matching navigation algorithm based on improved Siamese network is proposed. First, the space transformation network module is fused with the original Siamese network to improve the fitting ability between the scene features, and then the improved network is applied to the location and orientation algorithm of aircraft. The experimental results show that the Siamese network image matching navigation algorithm based on the fusion space transformation module enhances the ability to deal with the rotation and translation transformation between the real-time image and the reference image. Compared with the original Siamese network, the algorithm in this paper optimizes the similarity of two scenes from different angles by an average of 9.04%, thus expanding the adaptability of the algorithm. Compared with the traditional template matching algorithm, this algorithm has higher matching accuracy and stronger robustness when the angle of the real-time image changes and has certain practical application value in navigation algorithms.
Lidar Observations of the Fine-Scale Variability of Marine Stratocumulus Clouds

Abstract A Nd:YAG lidar system was flown aboard NASA's ER-2 high altitude aircraft. Observations of cloud top height were made with 70 m along-track and 7.5 m vertical-height resolution. The lidar data observed from an East Pacific stratocumulus cloud height deck revealed large cloud variability on 1–5 km scales. The cloud deck sloped upward from 700 to 1000 m in a northeast-southwest direction over a distance of 120 km. Vertical cloud top distributions were negatively skewed indicating flat-topped clouds. The dominant spectral peak of the cloud top variations was found at 4.5 km, which is 5 to 7 times the depth of the local boundary layer. No other peaks were significant in the average spectrum, The cloud layer was stable with respect to cloud top entrainment instability. The southwestern region of the study area was more prone to shear instability at cloud top than the northeastern region. The results of this study show that a lidar system is ideal to provide the topography of clouds and local boundary .
Stick‐Type Discharge Triboelectric Nanogenerator with Amplified Output Using a Conductive Spring

As technology develops over time, energy‐harvesting methods that generate sustainable energy have been highlighted worldwide. In energy harvesting, triboelectric nanogenerators (TENGs) have several advantages, such as a simple design, high efficiency, low cost, and accessibility. Although they are applied in various fields, TENGs have limitations regarding the low current output on the microampere scale due to a high surface charge, leading to air breakdown and field emission. In addition, TENGs are implemented under vacuum pressure with high mechanical input frequency to overcome the limitation. Nevertheless, the developed TENGs still retain critical problems, such as the inability to make packaging systems and device damage. This paper reports on the stick‐type discharge (SD) TENG that can provide an amplified current with outstanding durability by applying a conductive spring to solve the problem. Consolidating a dynamic electrode with an accumulated surface charge and low curvature spring and emitting a high electric field generate a milliampere current scale through electrons to flow directly with exceptional mechanical endurance. Thus, a multi‐SD‐TENG comprising four SD‐TENGs and a portable holder powers a warning light in daily life through a shaking motion.
Modèle d'approche de la houle par une méthode de réfraction-diffraction en coordonnées curvilignes

The wave propagation is followed in curvilinear orthogonal coordinates given by its rays and its crest, solutions of diffraction-refraction problem. This process is iterative as the metric is not known a priori. When the wave turn, the second derivative of wave height is thus always calculated along the crests. Propagation solutions are researched to compute the second derivative of height along the wave direction. The choice of the height envelope as variable enables us to use a space step commensurable with the wave length and to eliminate the solu- tion degradation along the lateral model boundaries. This method also enables to obtain a wave radiation condition on the fluid boundaries of agitation models.
Dual-Regression Retrieval Algorithm for Real-Time Processing of Satellite Ultraspectral Radiances

AbstractA fast physically based dual-regression (DR) method is developed to produce, in real time, accurate profile and surface- and cloud-property retrievals from satellite ultraspectral radiances observed for both clear- and cloudy-sky conditions. The DR relies on using empirical orthogonal function (EOF) regression “clear trained” and “cloud trained” retrievals of surface skin temperature, surface-emissivity EOF coefficients, carbon dioxide concentration, cloud-top altitude, effective cloud optical depth, and atmospheric temperature, moisture, and ozone profiles above the cloud and below thin or broken cloud. The cloud-trained retrieval is obtained using cloud-height-classified statistical datasets. The result is a retrieval with an accuracy that is much higher than that associated with the retrieval produced by the unclassified regression method currently used in the International Moderate Resolution Imaging Spectroradiometer/Atmospheric Infrared Sounder (MODIS/AIRS) Processing Package (IMAPP) retriev.
The H I extent and deficiency of spiral galaxies in the Virgo cluster

Neutral hydrogen observations mapping along the optical major axis have been made with the Arecibo 305-m telescope and flat feed system for 24 spiral galaxies in the Virgo cluster. Comparison of observed flux integrals with those obtained from a numerical convolution of the antenna beam pattern and an assumed H I surface density distribution yields a measure of an effective H I size, taken to be that radius interior to which lies 70% of the total H I mass. The neutral hydrogen properties of the Virgo cluster spirals have been compared with those of a similar sample of isolated galaxies. We find that, for a given optical diameter, a Virgo core galaxy has a smaller H I extent than its optical counterpart; we measure the ratio of the H I to optical Holmberg diameter d/sub Htsi//d/sub Ho/ to be 0.70 for the 19 galaxies within a five degree projected radius of the cluster center, whereas those outside show d/sub Htsi//d/sub Ho/ approx. =1.10. Using the relation derived between the optical linear diameter and the H I mass, we are able to define a H I deficiency parameter and find that the galaxies in the Virgo core are, on the average,more » H I deficient by a factor of 2.7 with respect to the isolated galaxies. The similarity of the relationship between the H I mass and the H I linear diameter, within the statistical errors, for both gas deficient and normal galaxies, implies that the linear extent of the H I distribution within a galaxy is well correlated with its total H I mass. The stripping mechanisms responsible for the H I deficiency observed in cluster galaxies, therefore, do not substantially alter the average H I surface density, but rather lower the H I mass and size to values expected for an optically smaller galaxy. The dependence of the H I deficiency on the velocity of a galaxy with respect to the cluster suggests that the mechanism responsible for the removal of the interstellar gas from the galaxy is the ram pressure sweeping of the intracluster gas. « less
Designing of Fractional Order PID Controller for Hard-To-Be-Control Plant with Time Delay

The flower pollination algorithm (FPA), one of the most efficient metaheuristic optimization search techniques, is applied to design an optimal fractional-order proportional-integral-derivative (FOPID or $\mathrm{P}\mathrm{I}^{\lambda}\mathrm{D}^{\mu}$) controller for a hard-to-be-control plant with time delay. FPA searches the 5 appropriate parameters of the controller to meet the response specifications of the plant. Results obtained by this procedure will be compared with those obtained by the conventional controller or integer-order proportional-integral-derivative (IOPID or PID) controller or the conventional controller. By comparison of unit step response, the optimal FOPID controller yields very satisfactory responses superior than the IOPID controller with faster response and very small steady-state error. MATLAB and FOMCON programs are used to conduct this research.
Quantum cohomology rings of Grassmannians and total positivity

We give a proof of a result of D. Peterson’s identifying the quantum cohomology ring of a Grassmannian with the reduced coordinate ring of a certain subvariety of GLn. The totally positive part of this subvariety is then constructed and we give closed formulas for the values of the Schubert basis elements on the totally positive points. We then use the developed methods to give a new proof of a formula of Vafa and Intriligator and Bertram for the structure constants (Gromov–Witten invariants). Finally, we use the positivity of these Gromov–Witten invariants to prove certain inequalities for Schur polynomials at roots of unity.