Miracle-dz/UniFAR-FTUs huggingface dataset:
Submicron particle deposition in pulmonary alveoli during cyclic breathing

The prediction of deposition eciency of submicron particles in the pulmonary alveoli has received special attention due to its importance for drug delivery systems and for assessing air pollutants health risks. In this work, the pulmonary alveoli of a healthy human are idealized by a three-dimensional honeycomb-like con guration and a fluid-structure interaction analysis is performed. In contrast to previous works in which the inlet ow rate is prede ned, in this model, a negative pressure is imposed on the outside surface of the alveolus which causes air to flow in and out of the alveolus. The resulting flow patterns con rmed that there was no circulation in the terminal alveolus. The predicted alveolar air flow was used to calculate the trajectories of submicron particles using the Lagrangian approach. Our ndings suggest that an accurate simulation requires including at least ten breathing cycles, considering a parabolic radial distribution of injected particles andcontinuous injection. The presented results show high deposition eciency for submicron sizes in the alveolar region if these particles can reach the alveolar region. Therefore, the vesicles technology in which particle agglomerates would be released after the vesicle reaching the alveoli is suggested for targeted drug delivery to the alveolar region.
A Virtuous Circle: Artificial Intelligence and Accessibility for Administrative Applications

In this paper, we suggest that accessibility is an emerging, underfulfilled legal requirement that presents not only a potential locus for activity but also an avenue for research. We describe a proof-of-concept use of machine-learning-based image classification as a managerial support tool for accessibility enhancement, and suggest directions for further research. Although this discussion focuses on the government information landscape in the United States, the adoption of the Web Content Accessibility Guidelines in the European Union extends its applicability.
New Insights on the Nordic Experience

This paper takes a fresh look at the analysis of labour market dynamics and argues that capital accumulation plays a fundamental role in shaping unemployment movements. This role has generally been examined by considering indirect transmission channels of the capital stock e ects, i.e. using variables like interest rates or investment ratios in the estimation of single-equation unemployment rate models. Here we advocate a di erent approach. We directly estimate the e ects of capital stock in the labour market by applying the chain reaction theory of unemployment, and we find that capital stock is a major determinant of unemployment in the Nordic countries. In particular, the di erent unemployment experiences of these economies derive from the temporary (albeit prolonged) negative shocks to capital stock growth in Denmark and Sweden, and the permanent downturn of capital stock growth in Finland. We are thus able to explain why the crisis of the early 1990s had a more accute impact in Finland than in its twin economy, Sweden.
Combinatorial Library of Ternary Polyplexes Enables Identification of Improved siRNA Nanocarriers for Rapid In Vivo Translation By:

A new library of ternary siRNA polyplexes formed of combinatorially combined pHresponsive polymers was developed and screened for gene silencing efficacy in vitro and in vivo. [2-(dimethylamino)ethyl methacrylate] (DMAEMA)and butyl methacrylate (BMA)-containing polymers were synthesized via reversible addition – fragmentation chain transfer (RAFT) polymerization. Ternary polyplexes were formed by varying the amounts and ratio of core-forming copolymers to corona-forming PEGylated, diblock copolymers during polyplex assembly. This library was developed such that structure-activity relationships of pH-responsive polymeric nanoparticles such as polyplex surface PEGylation density, size, stability, and endosomolysis could be systematically studied, and the relative importance of design parameters identified. The lead ternary polyplex formulation identified from multiparametric in vitro screening, DB-50B412, was optimally PEGylated with enough PEG to ensure colloidal stability (no change in size by DLS between 0 and 24 hr) and neutral surface charge (-1.86 mV) but had higher cell uptake (>90% positive cells) than the most densely PEGylated particles. The DB-50B412 polyplexes also incorporated the most hydrophobic and endosomolytic core-forming polymer, resulting in robust endosomolysis and in vitro siRNA silencing (~85% protein level knockdown) of the model gene luciferase. The potential efficacy of our lead ternary polyplex was further validated in vivo and benchmarked against binary polyplexes of the corona-forming PEGylated diblock. The DB50B412 polyplex exhibited a reduced level of renal clearance after intravenous administration,
Relax and Recover: Guaranteed Range-Only Continuous Localization

Range-only localization has applications as diverse as underwater navigation, drone tracking and indoor localization. While the theoretical foundations of lateration—range-only localization for static points—are well understood, there is a lack of understanding when it comes to localizing a moving device. As most interesting applications in robotics involve moving objects, we study the theory of trajectory recovery. This problem has received a lot of attention; however, state-of-the-art methods are of a probabilistic or heuristic nature and not well suited for guaranteeing trajectory recovery. In this letter, we pose trajectory recovery as a quadratic problem and show that we can relax it to a linear form, which admits a closed-form solution. We provide necessary and sufficient recovery conditions and in particular show that trajectory recovery can be guaranteed when the number of measurements is proportional to the trajectory complexity. Finally, we apply our reconstruction algorithm to simulated and real-world data.
What Role does Corporate Governance Play in the Intention to Use Cloud Computing Technology?

This paper aims to investigate the factors which promote the adoption of cloud-based technology. It strives for a better understanding of the impact of corporate governance on the adoption of this technology. This study concentrated on executives in companies where the use of cloud computing may give a competitive advantage. The main contribution of this work is to propose a model for the influence of corporate governance and other factors that determine the adoption of this technology. A questionnaire was prepared after taking into consideration the reviewed literature. The sample consisted of 164 technology companies from Southern Spain that already use the new economic models for digital solutions. The methodology used to analyze the structural model was the Structural Equation Model (SEM). The results of the survey showed the influence of Corporate Governance and the procedures and practices of the organization on the adoption of cloud computing and the associated business model. This study aims to point out the importance of corporate support and Knowledge Management for the correct and successful adoption of this technology and to show the effects on the new business model of billing for the use of available resources.
Case Study of a Domain Decomposition Method for Efficient Structural Analysis

Solving of large linear system of equations play important part in mathematical modeling using numerical methods such as Finite Element approximation. The case study is the problem of linear elasticity in 3D. A numerical example arising from a domain decomposition method will show the efficiency of iterative solvers for problems with multiple right hand sides. An effect of numerical stabilization of block iterative solvers is presented and discussed as well.
Global Adaptive Generative Adjustment

Many traditional signal recovery approaches can behave well basing on the penalized likelihood. However, they have to meet with the difficulty in the selection of hyperparameters or tuning parameters in the penalties. In this article, we propose a global adaptive generative adjustment (GAGA) algorithm for signal recovery, in which multiple hyperpameters are automatically learned and alternatively updated with the signal. We further prove that the output of our algorithm directly guarantees the consistency of model selection and the asymptotic normality of signal estimate. Moreover, we also propose a variant GAGA algorithm for improving the computational efficiency in the high-dimensional data analysis. Finally, in the simulated experiment, we consider the consistency of the outputs of our algorithms, and compare our algorithms to other penalized likelihood methods: the Adaptive LASSO, the SCAD and the MCP. The simulation results support the efficiency of our algorithms for signal recovery, and demonstrate that our algorithms outperform the other algorithms.
A Semidefinite Framework for the Sieve

We describe a semidefinite programming framework for proving upper bounds on concrete sifting problems, and show that the Large Sieve can be interpreted as a special case of this framework. With a small tweak, the Larger Sieve also falls into this framework. We compare the semidefinite approach to the linear programming approach (i.e., the general framework of the combinatorial sieve and the Selberg sieve), and show that it has a qualitative advantage in a toy case where the primes are completely independent from each other. No new sieve-theoretic bounds are proved.
First-principles Calculations of Structures and Micro-cracks of the Al-Ni Crystal Materials

The structures, elastic anisotropy, toughness, and Debye temperature of the Al-Ni crystal are analyzed by using the density functional theory: PW91. The results show that AlNi is the most anisotropic of all phase, and the Al3Ni2 is the most isotropic of all phase. In addition to Al3Ni and Al3Ni2 are brittle materials, other intermetallics are tougher materials. Among which, AlNi has the best toughness, and Al3Ni2 has the best brittleness. The study of Debye temperature suggests that Al3Ni has the highest Debye temperature, AlNi has the lowest Debye temperature. Introduction Aluminum alloy is a kind of extensive nonferrous metal material, which is widely used in aerospace, automobile, machinery manufacturing industry. Aluminum-nickel (Al-Ni) alloy has high-strength, lower density and oxidation resistance and corrosion resistance in a variety of aluminum-based alloys [1]. However, it has ductility which limits its application [2]. W.Lin and Tresa M. Pollock et al. [3] have found that the Al-Ni alloys have poor ductility at room temperature. Chan et al. [4] have found that toughness and ductility of Al-Ni alloy can be improved by grain refinement and alloying. The anisotropy of crystal is an important parameter to measure the mechanical properties of the material, It can let us know the cause of the micro-cracks in the material. The micro-structure and micro-cracks of the Al-Ni crystal should be widely attention. In this work, the structural, toughness, elastic anisotropy and Debye temperature will be investigated within the density functional theory (DFT) framework for Al-Ni crystal. Computational Details In this study, the Al-Ni phases are adopted from Ref. [5] The generalized gradient approximation (GGA) [6] with the Perdew-Wang (PW91) functional is adopted to describe the exchange and correlation interaction. The ultra-soft pseudo-potentials (USPP) methods are used to study the interactions between ions and valence electrons [7]. A plain wave cutoff energy is set to 490eV. Brillouin zone intergations are set to a Monkhorst-Pack k-point mesh [8], the k-point mesh of each cell has been sampled by 2×2×3, 4×4×4, 10×10×10, 2×2×4, 4×4×4 grids for Al3Ni, Al3Ni2, AlNi, Al3Ni5, AlNi3, respectively. The elastic anisotropy can be described by defining universal index(AU) [9]. AU=(5GV/GR+BV/BR-6)×100 (1) BV=1/9(C11+C22+C33)+2/9(C12+C23+C13) (2) 3rd Annual International Conference on Advanced Material Engineering (AME 2017) Copyright © 2017, the Authors. Published by Atlantis Press. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Advances in Engineering Research, volume 110
LGBTIQ Parenthood in Croatia: Experiences and Perceptions

A growing number of lesbian, gay, bisexual, trans, intersex and queer (LGBTIQ1) people want to have or already have children (e.g. Goldberg and Allen, 2013; Pew Research survey, 2013). Scientific research published to date, including longitudinal and national probability studies, provides strong evidence that parental sexual orientation is not related to parenting effectiveness (adams and Light, 2015; Crouch et al., 2014; Goldberg and Allen, 2013; Manning, Fettro and Lamidi, 2014; Vučković Juroš, 2017). In other words, children growing up with LGBTIQ parents are similar to children living with heterosexual parents as concerns many relevant outcomes, including children’s wellbeing, academic achievement, cognitive development, social skills and mental health. Although societies differ in levels of formal or informal acknowledgement and in terms of the acceptance of LGBTIQ people, negative reactions are easily provoked when discussing LGBTIQ parenthood (Takács, Szalma and Bartus, 2016). Unlike families with heterosexual parents, families with LGBTIQ parents largely lack legal as well as social recognition and support (Takács and Szalma, 2011). They are also often exposed to stigmatization and discrimination (Takács, 2015). These negative experiences can have a broad negative impact on the wellbeing of LGBTIQ people and their children (Appell, 2003; Bos et al., 2004; Patterson, Fulcher and Wainright, 2002; Weber, 2010). Since the early 2000s, Croatian society has witnessed significant formal and societal changes in the direction of greater acceptance and acknowledgement of LGBTIQ people and their rights (Jurčić, 2018). Nonetheless, public discussions over the family lives of LGBTIQ people remain mostly negative and frequently do not move beyond expressions of personal attitudes and prejudice (Hodžić and Štulhofer, 2017). In general, public levels of recognition and knowledge about the families of LGBTIQ individuals are low (Kamenov, Huić and Jelić, 2017; Jugović and Ogresta, 2017). Furthermore, scientific studies on sexual orientation and gender identities are very rare within the Croatian context. While there are many in-
GKM GRAPHS INDUCED BY GKM MANIFOLDS WITH SU (ℓ + 1)-SYMMETRIES

A GKM manifold is a 2m-dimensional manifold M equipped with an effective T action whose one and zero dimensional orbits have the structure of a graph, where n ≤ m. Using the effectiveness of the action and the differentiable slice theorem around zero dimensional orbits (i.e., fixed points), we see that the induced graph of a 2m-dimensional GKM manifold must be an m-valent graph, i.e., each vertex has just m outgoing edges. Moreover, each outgoing edge can be labeled by using the tangential representation (the slice representation around fixed points) of T -action, called an axial function. An m-valent graph labeled by an axial function is called a GKM graph (see Section 2 or [8, 12] for more detail). In this article, we introduce some results in the forthcoming paper [16] which is devoted to studying the extended actions of GKM manifolds (or GKM manifolds with large symmetries). In particular, we introduce the results for GKM graphs induced by the GKM manifolds with SU(l+1)-symmetries under some assumptions, motivated by the Masuda’s work [19] and the Wiemeler’s work [23].
Machine Learning for Location and Orientation Fingerprinting in MIMO WLANs

To detect the position and the orientation of a mobile device within a Wireless Local Area Network (WLAN) covered by multiple access points (APs), the intrinsic properties of multiple-input multiple-output (MIMO) channels are used linking the received signal strength indicators (RSSIs) to the distance and exploiting the received signal correlation structures. Location and orientation fingerprinting is a map based positioning solution that stores for a given orientation past measurements of RSSIs at known reference/grid points in a database that is later used to localize a mobile device at an unknown location and with unknown orientation to the closest reference point. This paper focuses on processing the RSSI data vectors from multiple receiving antennas on a downlink by applying the core tools of Machine Learning (ML) classification methods to evaluate the effects of MIMO RSSI meta-data when capturing 802.11n/ac packets using commodity hardware. Specifically, the paper provides insights into the design of the overall location fingerprinting system operating with new WiFi physical link layer protocols. To verify the operation of the proposed system, experimental results are presented to investigate the impact of different factors, like the number of receive antennas, affecting the estimation accuracy for the location and the orientation of mobile user.
Seasonal and Ontogenic Shifts in Microhabitat Selection by Fishes in the Shallow Waters of the Detroit River, a Large Connecting Channel

Abstract We examined the relationship between microhabitat variables and fish distributions in a large connecting channel, the Detroit River. Fishes were sampled by boat seine at 60 sites in shallow (<2.5 m) Canadian waters in May, July, and September 2004. Length-frequency distributions were used to separate species into small- and large-species size categories. Fish–microhabitat associations were examined by applying canonical correspondence analysis separately for each season. Small fishes were often more strongly associated with microhabitat variables than large conspecifics. For example, small centrarchids were more strongly associated with complex macrophytes than large centrarchids in the spring; however, this pattern varied among seasons. We attribute the stronger microhabitat associations of small fishes to predator avoidance. Small-bodied species also selected habitats that provided protection against predation: The spotfin shiner Cyprinella spiloptera preferred shallow water, and the round goby.
Towards an Alternative to Neo-Liberalism: Class, Institutional and Organizational Analysis

Over-reliance upon class analysis has obscured analysis of more universal human concerns related to human needs and rights as well as the natural environment. Marxism and social democracy’s reliance upon state socialism has not proven to be a viable alternative, nor has class struggle been a sufficient force producing social change. A viable alternative should counterpoise human rationality and democratic processes against unrestrained market forces. A more sophisticated form of policy analysis is needed which can rely upon class, organizational, and institutional analysis as well as analysis of inequalities based upon gender, race and ethnicity in order to ascertain the best mix of public, nonprofit and for-profit social production needed within each policy domain in order to meet universal human needs in a culturally informed manner and in a way consistent with universal human rights.
Treatment of chronic heart failure in adults at a referral hospital in Kenya: adverse drug reactions and determinants of adherence

Background : Chronic Heart Failure is a major health problem with a prevalence of between 1 and 12% in USA and Europe, and approximately 5.7% in Sub-Saharan Africa, and has socio-economic relevance owing to its high prevalence, mortality and impact on young economically active individuals. In 1999 chronic heart failure constituted 3.3% of all medical admissions at Kenyatta National Hospital. Objective: The purpose of the current study was to determine factors that affect adherence to treatment among patients with Chronic Heart Failure at Kenyatta National Hospital and assess any association between any such factors Methodology: This was a descriptive cross-sectional study involving patients >18 years diagnosed with Chronic Heart Failure at Kenyatta National Hospital. Eighty three eligible and consenting study participants were recruited into the study using a convenient sampling technique. Data were collected by means of an interviewer administered questionnaire adapted from the Revised HF Adherence Questionnaire. Results: Data from 83 patients was analyzed majority (n=51, 61.4%) of whom were women. The age of the patients ranged from 18 to 80 years with the majority (n= 37, 44.6%), between 21-40 years. Majority (n=58, 68.9%) of the patients considered appointment keeping, compliance to medication (n= 64, 77.1%), dietary restriction (n=59, 72%), regular exercise (n=49 59.0%), smoking cessation (n=59, 71%), and alcohol cessation (n=58, 69.9%) as very important. Fifty three (63.9%) respondents had not failed to take their medicines at any time. Majority (n=72, 86.8%) of the study participants were aware of the disease condition they were suffering from while valvular heart disease was the commonest comorbidity (n= 17 27.9%). The study revealed an association between sex and some adverse drug reactions using Pearson χ² test through bivariate analysis. Sleep disturbances and nausea occurred more in males than females while headache and drowsiness were more prevalent in females and in both cases the relationships were statistically significant (p< 0.05) Conclusions: Adherence to medicines among patients with Chronic Heart Failure is reasonably high at Kenyatta National Hospital despite patients’ knowledge level about the condition being generally low. Valvular heart disease was the most common comorbidity while hyponatremia was the most prevalent electrolyte disturbance, and tachycardia, vomiting and rash the most common adverse drug effects. Key words Chronic heart failure; adherence; compliance; adverse drug reactions.
Retirement Savings: Choosing a Withdrawal Rate That Is Sustainable

16 To help in the selection of a withdrawal rate, the following sections provide information on the historical success of various withdrawal rates from portfolios of stocks and bonds. If a withdrawal rate proves too high based on historical year-to-year returns, then it seems likely that the rate will not be sustainable during future periods. Conversely, historically sustainable withdrawal rates are more likely to have a high probability of success in the future.
Day and Night Closed-Loop Control in AdultsWith Type 1 Diabetes A comparison of two closed-loop algorithms driving continuous subcutaneous insulin infusion versus patient self-management

YOERI M. LUIJF, PHD J. HANS DEVRIES, PHD KOOS ZWINDERMAN, PHD LALANTHA LEELARATHNA, MRCP MARIANNA NODALE, MSC KAREN CALDWELL, RN KAVITA KUMARESWARAN, PHD DANIELA ELLERI, MD JANET M. ALLEN, RN MALGORZATA E. WILINSKA, PHD MARK L. EVANS, MD ROMAN HOVORKA, PHD WERNER DOLL, MS MARTIN ELLMERER, PHD JULIA K. MADER, MD ERIC RENARD, PHD JEROME PLACE, MS ANNE FARRET, MD CLAUDIO COBELLI, PHD SIMONE DEL FAVERO, PHD CHIARA DALLA MAN, PHD ANGELO AVOGARO, PHD DANIELA BRUTTOMESSO, PHD ALESSIO FILIPPI, MD RACHELE SCOTTON, MD LALO MAGNI, PHD GIORDANO LANZOLA, PHD FEDERICO DI PALMA, PHD PAOLA SORU, MS CHIARA TOFFANIN, MS GIUSEPPE DE NICOLAO, PHD SABINE ARNOLDS, MD CARSTEN BENESCH, PHD LUTZ HEINEMANN, PHD ON BEHALF OF THE AP@HOME CONSORTIUM