Miracle-dz/UniFAR-FTUs huggingface dataset:
Naloxone distribution and possession following a large‐scale naloxone programme

Abstract Aims To examine uptake following a large‐scale naloxone programme by estimating distribution rates since programme initiation and the proportion among a sample of high‐risk individuals who had attended naloxone training, currently possessed or had used naloxone. We also estimated the likelihood of naloxone possession and use as a function of programme duration, individual descriptive and substance use indicators. Design (1) Distribution data (June 2014–August 2017) and date of implementation for each city and (2) a cross‐sectional study among a sample of illicit substance users interviewed September 2017. Setting Seven Norwegian cities. Participants A total of 497 recruited users of illegal opioids and/or central stimulants. Measurements Primary outcomes: naloxone possession and use. Random‐intercepts logistic regression models (covariates: male, age, homelessness/shelter use, overdose, incarceration, opioid maintenance treatment, income sources, substance use indicators, programme duration). Findings Overall, 4631 naloxone nasal sprays were distributed in the two pilot cities, with a cumulative rate of 495 per 100 000 population. In the same two cities, among high‐risk individuals, 44% and 62% reported current naloxone possession. The possession rates of naloxone corresponded well to the duration of each participating city's distribution programme. Overall, in the six distributing cities, 58% reported naloxone training, 43% current possession and 15% naloxone use. The significant indicators for possession were programme duration [adjusted odds ratios (aOR) = 1.44, 95% confidence interval (CI = 0.82–2.37], female gender (aOR = 1.97, 95% CI = 1.20–3.24) and drug‐dealing (aOR = 2.36, 95% CI = 1.42–3.93). The significant indicators for naloxone use were programme duration (aOR = 1.49 95%, CI = 1.15–1.92), homelessness/shelter use (aOR = 2.06, 95% CI = 1.02–4.17), opioid maintenance treatment (OMT) (aOR = 2.07, 95% CI = 1.13–3.78), drug‐dealing (aOR = 2.40, 95% CI = 1.27–4.54) and heroin injecting (aOR = 2.13, 95% CI = 1.04–4.38). Conclusions A large‐scale naloxone programme in seven Norwegian cities with a cumulative distribution rate of 495 per 100 000 population indicated good saturation in a sample of high‐risk individuals, with programme duration in each city as an important indicator for naloxone possession and use.
HAP2/GCS1: Mounting evidence of our true biological EVE?

Sex has consequences—indeed, where would we be without it? Yet for all its importance, remarkably little is known about how sex evolved, why it has persisted, or even what mechanisms allow sperm–egg fusion to occur. Fortunately, answers to these questions are beginning to emerge with studies of hapless 2/generative cell specific1 (HAP2/GCS1), a molecular machine that promotes gamete fusion in organisms ranging from protists to flowering plants and insects. In studies by Fedry and colleagues, key structural features of the HAP2 protein are revealed for the first time, lending new insights into its mode of action and reinforcing its relationship to viral proteins that accomplish a similar task and may be intimately linked to the origins of cell–cell fusion events (including sexual reproduction) across evolutionary time.
Electrical Conductivity and Optical Properties of Pulsed Laser Deposited LaNi5 Nanoscale Films

This work presents pulsed laser deposition as a method to obtain unoxidized LaNi5 nanoscale films and describes their temperature and thickness dependent electrical conductivity and the spectral dispersions of some optical properties. AB5-type rare earth element (REE)-nickel compounds are currently studied from both theoretical and practical points of view. Special challenges are posed during the preparation of these nanomaterials, which can be overcome using finely tuned parameters in a preparation process that always involves the use of high energies. Film deposition was made by laser—induced vaporization, with short and modulated impulses and electro–optical tuning of the quality factor, mainly on glass and one SiO2 substrate. Deposition geometry dependent linear thickness increase, between 1.5–2.5 nm per laser burst, was achieved. Film structures and phase compositions were determined using XRD and discussed in comparison with films obtained by similar deposition procedures. Temperature and scale dependent properties were determined by studying electrical conductivity and optical properties. Electrical conductivity was measured using the four-probe method. The observed semiconductor-like conductivity for film thicknesses up to 110 nm can be explained by thermal activation of electrons followed by inter-insular hopping or quantum tunneling, which, on the other hand, modulates the material’s native metallic conductance. Films with thicknesses above this value can be considered essentially metallic and bulk-like. The spectral behaviors of the refractive index and absorption coefficient were deduced from differential reflectance spectroscopy data acquired on a broad ultraviolet, visible, near- and mid-infrared (UV-VIS-NIR-MIR) domain, processed using the Kramers-Krönig formalism. Their study led to the identification of the allowed interband transitions. Electronic behavior in the energy bands near the Fermi level and in the surface and interface-states was described, discussing the differences between experimental data and the classical free-electron theoretical model applied for the bulk intermetallic alloy, in correlation with theoretical optical properties or experimental X-ray photoelectron spectroscopy (XPS) results from references. However, the dielectric-like shape of the reflectance of the thinnest film was in accordance with the Lorentz–Drude model.
Gradient porous fibrous scaffolds: a novel approach to improving cell penetration in electrospun scaffolds

Electrospinning is an increasingly popular technique to generate 3D fibrous tissue scaffolds that mimic the submicron sized fibers of extracellular matrices. A major drawback of electrospun scaffolds is the small interfibrillar pore size, which normally prevents cellular penetration in between fibers. In this study, we introduced a novel process, based on electrospinning, to manufacture a unique gradient porous fibrous (GPF) scaffold from soy protein isolate (SPI). The pore sizes in the GPF scaffolds gradually increase from one side of the scaffold to the other, ranging from 7.8 ± 2.5 μm in the small pore side, 21.4 ± 10.3 μm in the mid layer to 58.0 ± 23.6 μm in the large pore side. The smallest pores of the GPF scaffolds appeared to be somewhat larger than those in conventionally electrospun SPI scaffolds (4.2 ± 1.3 μm). Hydrated GPF scaffolds exhibited J-shaped stress–strain curves, reminiscent of those for soft biological scaffolds. Attachment, spreading, and proliferation of human dermal fibroblasts (HDFB) were supported on both the small and the large pore sides of the GPF scaffolds. Cultured HDFB and murine RAW 264.7 macrophages penetrated significantly deeper (98.7 ± 24.2 μm and 53.3 ± 9.6 μm, respectively) into the larger pores than when seeded onto the small pore side of GPF scaffolds (22.8 ± 6.2 μm and 25.7 ± 7.3 μm) and control SPI scaffolds. (11.3 ± 3.8 μm and 15.3 ± 3.1 μm). This study introduces a novel fabrication technique, which, by convergence of several biofabrication technologies, produces scaffolds with enhanced cellular penetration.
Implicit Surface Reconstruction and uniform Sampling by Striped Marching Triangles

The synthesis of computer models from real objects is a usual procedure in medical image processing and reverse engineering. In both cases, the main issues are to reach a topologically consistent and geometrically precise object reconstruction. Implicit surfaces provide a solution to this problem. They define a smooth surface surrounding objects which must be polygonized for an efficient visualization. Due to the increasing size of the application generated data, it becomes necessary to use precise and efficient methods. This work presents a modified method of implicit surface polygonization based on “Marching Triangles”. This modification assures the topological consistency with the initial dataset during the progressive reconstruction of the surface, avoiding overlapping triangles. In addition, a comparison of our method with the marching cubes and the adaptive skeleton climbing algorithms is provided.
An Adaptive Cooperative Transmission Algorithm for Multi-stream in Heterogeneous Multipath Networks

In heterogeneous multipath networks, the actual throughput is far lower than the sum of the available bandwidth of each path in most these multipath transmission protocols. Motivated by that, an adaptive cooperative transmission algorithm based on bandwidth estimation is proposed in this paper. The algorithm named BD-DAST aims to monitor the actual throughput of each path periodically and segment adaptively the untransmitted data. After that, these data will be pre-allocated to the corresponding path for transmission. The algorithm can contribute to the adaptive adjustment of the data granularity and the expectation of network throughput increase. The experiments and evaluations prove that the BD-DAST algorithm can significantly improve the total throughput in the heterogeneous multipath networks.
A 0.55THz Y-Vector Network Configured Beam Steering Phased Array in CMOS Technology

A Y-vector oscillator network is devised to configure (sub)-mm-wave/terahertz (THz) beamforming systems with minimized footprint and energy consumption. It requires no traditional adjustable phase shifter at multi-channel front end which usually suffer from high insertion loss at these frequencies. A compact (1.4mm2) CMOS lx4 Beam Steering Phased Array (BSPA) based on this network is validated at 0.55THz with $\pm \mathbf{30}^{\circ}$ steering angle range. This is the first monolithic BSPA reported beyond 0.5THz.
Physiological reactivity in response to a fear-induced virtual reality experience: Associations with psychopathic traits.

Despite the longstanding discussion around the link between psychopathy and fearlessness, few studies have explicitly tested this association, and results have been mixed. This may be due, in part, to the lack of specificity in fear assessment. Further, the relation between psychopathy and fear may be better understood using the two-factor model because, in theory, fear has opposing associations with interpersonal-affective (Factor 1) and impulsive-antisocial (Factor 2) traits. The present study aimed to test if the two factors of psychopathy are deferentially related to fear reactivity. To examine this, we collected sympathetic (SNS; skin conductance) and parasympathetic (PNS; respiratory sinus arrhythmia) nervous system reactivity to an interactive virtual reality horror video in a nonclinical sample (N = 103). Also, we included measures of emotional reactivity to fear and self-report of situational fear. Results indicated that coinhibition (i.e., low PNS and SNS) of the two physiological systems predicted Factor 1, suggesting that individuals high on Factor 1 showed little change in both branches of the autonomic nervous system in response to fear. In contrast, Factor 2 was predicted by high PNS reactivity, suggesting a vulnerability to emotion dysregulation. On emotional reactivity, Factor 1 was related to feeling happier after the fear condition, whereas Factor 2 was related to feeling less in control. Factor 1 was inversely associated with situational fear, specifically, lower scores of social phobias, fear of aggression, and physical injury. In summary, the results provide evidence that psychopathy is related to fearlessness; however, this is unique to the personality features of psychopathy.
Unveiling and Quantifying Facebook Exploitation of Sensitive Personal Data for Advertising Purposes

The recent European General Data Protection Regulation (GDPR) restricts the processing and exploitation of some categories of personal data (health, political orientation, sexual preferences, religious beliefs, ethnic origin, etc.) due to the privacy risks that may result from malicious use of such information. The GDPR refers to these categories as sensitive personal data. This paper quantiﬁes the portion of Facebook users in the European Union (EU) who were labeled with interests linked to potentially sensitive personal data in the period prior to when GDPR went into effect. The results of our study suggest that Facebook labels 73% EU users with potential sensitive interests. This corresponds to 40% of the overall EU population. We also estimate that a malicious third party could unveil the identity of Facebook users that have been assigned a potentially sensitive interest at a cost as low as e 0.015 per user. Finally, we propose and implement a web browser extension to inform Facebook users of the potentially sensitive interests Facebook has assigned them.
Intensity and Phase Modulators at 1.55 μm in GaAs/AlGaAs Layers Directly Grown on Silicon

We report for the first-time electro-optic phase and amplitude modulators in GaAs/AlGaAs epitaxial layers grown on misaligned silicon substrates containing germanium buffer layers. Epilayer has a <italic>npin</italic> doping profile and is equivalent to a <italic>pin</italic> diode. The 4-mm long electrode Mach–Zehnder modulators have 7.4- and 3.6-V <italic>V<sub>π</sub></italic> under single-arm and push–pull drive conditions corresponding to 1.5 ± 0.1 V-cm modulation efficiency. Data on 7-mm long electrode Fabry–Perot phase modulators indicate 2.3-V Mach–Zehnder modulators are possible. These data also indicate less than 1-dB/cm on-chip propagation loss under 5-V reverse bias.
Isolation and characterization of microsatellite loci for Prunus mongolica (Rosaceae)

Premise of the Study Microsatellite primers were developed in Prunus mongolica (Rosaceae), a relict flora endemic in arid areas of the Asian interior, to investigate the genetic diversity, phylogeography, population structure, and history of the species. Methods and Results Fifty‐one microsatellite loci, including di‐, tri‐, and tetranucelotide repeats, were identified using transcriptome sequencing and bioinformatic screening. The number of alleles ranged from seven to 11 and the levels of observed and expected heterozygosity ranged from 0.545 to 1.000 and 0.600 to 0.989, respectively. Most of the primers also amplified in a group of congeneric species (P. triloba, P. davidiana, P. persica, P. cerasifera, and P. serrulata). Conclusions This set of microsatellite loci is useful for studying the genetic diversity of P. mongolica. In addition, they can also be used to investigate the population structure, phylogeography, and landscape genetic patterns of congeneric species.
Constructionist learning in digital archives education: Student perceptions of effectiveness

This paper explores if a constructionist learning approach to digital archives education can positively influence student perceptions of their learning. Constructionism is a learning theory that places students in the role of designers and emphasizes creating physical artifacts in a social environment (Papert, 1980, 1991; Kafai, 2006). This theory is used in the instructional design of the Digital Archives Creation Project (DACP), which is a major component of a new digital archives course offered to a class of students enrolled in a MSLIS program. Results indicate that students perceived strong increases in their learning because of their engagement in the DACP, particularly in terms of their skills, confidence, understanding of topics covered in other courses, and overall understanding. Factors that influenced these increases include the collaborative teamwork, the role of the facilitator or instructor, and individual effort. Results indicate that a constructionist pedagogical approach holds great promise for LIS education, yet further research is required.
Learning-based Automatic Parameter Tuning for Big Data Analytics Frameworks

Big data analytics frameworks (BDAFs) have been widely used for data processing applications. These frameworks provide a large number of configuration parameters to users, which leads to a tuning issue that overwhelms users. To address this issue, many automatic tuning approaches have been proposed. However, it remains a critical challenge to generate enough samples in a high-dimensional parameter space within a time constraint. In this paper, we present AutoTune–an automatic parameter tuning system that aims to optimize application execution time on BDAFs. AutoTune first constructs a smaller-scale testbed from the production system so that it can generate more samples, and thus train a better prediction model, under a given time constraint. Furthermore, the AutoTune algorithm produces a set of samples that can provide a wide coverage over the high-dimensional parameter space, and searches for more promising configurations using the trained prediction model. AutoTune is implemented and evaluated using the Spark framework and HiBench benchmark deployed on a public cloud. Extensive experimental results illustrate that AutoTune improves on default configurations by 63.70% on average, and on the five state-of-the-art tuning algorithms by 6%-23%.
Reflections on FDA Draft Guidance for Products Containing Nanomaterials: Is the Abbreviated New Drug Application (ANDA) a Suitable Pathway for Nanomedicines?

The US Food and Drug Administration (FDA) recently released a draft guidance for industry titled “Drug Products, Including Biological Products, that Contain Nanomaterials. ” The FDA’s attention to the unique safety and efficacy aspects of drugs containing nanomaterials is commendable. This Draft Guidance succeeds in acknowledging the complexity of these products, as well as the challenges associated with approving safe and therapeutically equivalent complex generic versions. However, the challenge posed by the manufacturing process for drugs containing nanomaterials is insufficiently addressed. The critical quality attributes of such products cannot be properly defined, and therefore it is not possible to design informative comparative physicochemical assessments for equivalence. As a consequence, the 505(j) Abbreviated New Drug Application (ANDA) pathway, currently advised as the standard from the FDA, is not suitable for the approval of complex generic products. Drawing from the successful story of biologics, we propose instead a stepwise totality-of-evidence approach, demonstrating similarity and including clinical studies when deemed necessary, as an appropriate alternative to the 505(j) ANDA pathway.
DIBL–Compensated Extraction of the Channel Length Modulation Coefficient in MOSFETs

In this brief, a new channel length modulation (CLM) extraction method is proposed. The main innovation of this approach is that the extracted value of CLM is not artificially inflated by the contribution of the drain-induced barrier lowering (DIBL), which allows discriminating between the two phenomena. In this method, the transistor gain is measured by using the source-measurement unit in a forced current mode. It is demonstrated that the CLM coefficient can be extracted by the linear regression of the inverse of the gain with respect to the current-over-transconductance ratio, corrected for series resistances. This method is later applied and validated on a planar bulk 65-nm CMOS technology.
Clinical Name Entity Recognition Based on Recurrent Neural Networks

In this paper, we propose a novel approach for clinical name entity recognition based on deep machine learning architecture. The proposed scheme based on two different deep learning architectures: the feed forward networks (FFN), and the recurrent neural network (RNN), allow significant improvement in performance, in terms of different performance measures, including precision, recall and F-score, when evaluated with the CLEF 2016 Challenge task 1 A dataset corresponding to Clinical Nursing Handover. It was possible to achieve an F-score of 66% with RNN architecture, which was higher than most of the other participating systems in the Challenge task.
The Deconfounded Recommender: A Causal Inference Approach to Recommendation

The goal of a recommender system is to show its users items that they will like. In forming its prediction, the recommender system tries to answer: "what would the rating be if we 'forced' the user to watch the movie? " This is a question about an intervention in the world, a causal question, and so traditional recommender systems are doing causal inference from observational data. This paper develops a causal inference approach to recommendation. Traditional recommenders are likely biased by unobserved confounders, variables that affect both the "treatment assignments" (which movies the users watch) and the "outcomes" (how they rate them). We develop the deconfounded recommender, a strategy to leverage classical recommendation models for causal predictions. The deconfounded recommender uses Poisson factorization on which movies users watched to infer latent confounders in the data; it then augments common recommendation models to correct for potential confounding bias. The deconfounded recommender improves recommendation and it enjoys stable performance against interventions on test sets.
"If I press delete, it's gone" - User Understanding of Online Data Deletion and Expiration

In this paper, we present the results of an interview study with 22 participants and two focus groups with 7 data deletion experts. The studies explored understanding of online data deletion and retention, as well as expiration of user data. We used different scenarios to shed light on what parts of the deletion process users understand and what they struggle with. As one of our results, we identiﬁed two major views on how online data deletion works: UI-Based and Backend-Aware (further divided into levels of detail). Their main difference is on whether users think beyond the user interface or not. The results indicate that communicating deletion based on components such as servers or “the cloud” has potential. Furthermore, generic expiration periods do not seem to work while controllable expiration periods are preferred.
Electric-Field-Triggered Electromagnetic Polarizations in the Close-Packed Fe at C Nanocapsules

We investigated microwave absorption properties of the close-packed Fe at C nanocapsules under an external electric-field stimulus. The results indicate that the reflection parameter (<inline-formula> <tex-math notation="LaTeX">$S_{11}$ </tex-math></inline-formula>) linearly increases as the applied voltage ranging from 0 to 12 V at 18 to 26.5 GHz (<inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-band) frequencies, while the transmission parameter (<inline-formula> <tex-math notation="LaTeX">$S_{21}$ </tex-math></inline-formula>) remains constant. Such tunability is a consequence of the energy transfer between the permeability and the permittivity, physically originating from the multiple dielectric polarizations at the core at shell interfaces, ascribed to the electric-field induced asymmetric distribution of localized charge. The present finding might open up a new avenue for designing smart microwave absorbers targeted to complex serving environments.