Miracle-dz/UniFAR-FTUs huggingface dataset:
Ion-implanted silver nanoparticles for metal-enhanced fluorescence

Metal Enhanced Fluorescence (MEF) has promising applications in the field of optical displays, bio-sensing and photodynamic therapy. In this work, we exploit the plasmons of embedded silver nanoparticles (Ag NPs) fabricated by ion implantation to enhance the fluorescence of Coumarin515 dye (C515) via MEF. Ion Implantation of 70 keV Ag ions in quartz matrix at different fluences was carried out to synthesize Ag nanoparticles inside quartz matrix. The formation of Ag NPs is characterized by the optical absorption measurements and approximate sizes of Ag NPs was obtained from the fitting of the optical absorption spectra with Mie theory calculations. Rutherford Backscattering Spectrometry (RBS) measurement was used to obtain the depth profile and concentration Ag within the substrate. From the RBS results, it was determined that front edge of the layer containing Ag was formed at an average depth of 16 nm below the surface, which closely agreed with Stopping and Range of Ions in Matter (SRIM) calculations. Increase in the size of the NPs is observed as the fluence of the Ag within the substrate is increased. The MEF of drop casted C515 dye was studied using steady-state emission and excitation spectra measurements. Fluorescence enhancement factor ranging from 1.0 to 2.1 with a maximum enhancement for the largest size NP was obtained. The observed MEF was ascribed to a combination of plasmon enhancement with larger nanoparticles and to increased plasmonic hot spots.Metal Enhanced Fluorescence (MEF) has promising applications in the field of optical displays, bio-sensing and photodynamic therapy. In this work, we exploit the plasmons of embedded silver nanoparticles (Ag NPs) fabricated by ion implantation to enhance the fluorescence of Coumarin515 dye (C515) via MEF. Ion Implantation of 70 keV Ag ions in quartz matrix at different fluences was carried out to synthesize Ag nanoparticles inside quartz matrix. The formation of Ag NPs is characterized by the optical absorption measurements and approximate sizes of Ag NPs was obtained from the fitting of the optical absorption spectra with Mie theory calculations. Rutherford Backscattering Spectrometry (RBS) measurement was used to obtain the depth profile and concentration Ag within the substrate. From the RBS results, it was determined that front edge of the layer containing Ag was formed at an average depth of 16 nm below the surface, which closely agreed with Stopping and Range of Ions in Matter (SRIM) calculations. I.
Explaining the Good Governance of Agricultural Surface Water Resources in the Gawshan Watershed Basin, Kermanshah, Iran

The purpose of this study was to explain the current water governance at Gawshan Watershed Basin in Kermanshah Province and then provide an alternative conceptual framework for good governance of water resources at the basin scale. Participants were selected purposefully among the representatives of rival groups. Participatory workshop technique was used to collect data with the aid of interviews and focus group discussions. Analysis of the interviews led to classification of the challenges of water governance into several categories. These include the lack of participation, fairness, accountability, responsiveness, legitimacy, transparency and consensus-oriented processes. Then, water governance solutions were extracted based on the consensus among the participants. These include farmers’ contribution to decisionmaking processes regarding agricultural water consumption, empowering the local people to negotiate and manage conflicts, establishing a participatory mechanism to manage water conflict, holding training courses and workshops for staff to get acquainted with the principles of good governance, creating transparent and accessible information system by agricultural water section, and holding education-extension courses to increase information and awareness of the stakeholders in line with responsibility. Finally, a framework for good governance of water resources in the watershed basin was drawn up after linking the concepts.
Service Provisioning for Multi-source IoT Applications in Mobile Edge Computing

We are embracing an era of Internet of Things (IoT). The latency brought by unstable wireless networks caused by limited resources of IoT devices seriously impacts the quality of services of users, particularly the service delay they experienced. Mobile Edge Computing (MEC) technology provides promising solutions to delay-sensitive IoT applications, where cloudlets (edge servers) are co-located with wireless access points in the proximity of IoT devices. The service response latency for IoT applications can be significantly shortened due to that their data processing can be performed in a local MEC network. Meanwhile, most IoT applications usually impose Service Function Chain (SFC) enforcement on their data transmission, where each data packet from its source gateway of an IoT device to the destination (a cloudlet) of the IoT application must pass through each Virtual Network Function (VNF) in the SFC in an MEC network. However, little attention has been paid on such a service provisioning of multi-source IoT applications in an MEC network with SFC enforcement. In this article, we study service provisioning in an MEC network for multi-source IoT applications with SFC requirements and aiming at minimizing the cost of such service provisioning, where each IoT application has multiple data streams from different sources to be uploaded to a location (cloudlet) in the MEC network for aggregation, processing, and storage purposes. To this end, we first formulate two novel optimization problems: the cost minimization problem of service provisioning for a single multi-source IoT application, and the service provisioning problem for a set of multi-source IoT applications, respectively, and show that both problems are NP-hard. Second, we propose a service provisioning framework in the MEC network for multi-source IoT applications that consists of uploading stream data from multiple sources of the IoT application to the MEC network, data stream aggregation and routing through the VNF instance placement and sharing, and workload balancing among cloudlets. Third, we devise an efficient algorithm for the cost minimization problem built upon the proposed service provisioning framework, and further extend the solution for the service provisioning problem of a set of multi-source IoT applications. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms are promising.
CO2 regulates phase transition of sodium oleate and 3-(diethylamino)-propylamine in aqueous solution

ABSTRACT We reported that the phase conversion of the micelles in aqueous solution prepared by sodium oleate (NaOA) and 3-(diethylamino)-propylamine (DEAPA) in the presence of carbon dioxide. This micellar structure is very sensitive to CO2 and the pH value of the solution is continuously reduced with the continuous introduction of carbon dioxide. When pH > 10.2, the mixed solution of NaOA and DEAPA is mainly in the form of spherical micelles; when the 10.2 > pH > 9.6, the mixed solution mainly in the worm-like micelles (WLM), where the solution has a significant viscosity change; when the 9.6 > pH > 9.1, the NaOA and DEAPA mixed solution becomes the aqueous two-phase system (ATPS), which is composed of two layers, the upper layer is the vesicle structure and the lower layer is the WLM structure; when the pH between 9.1 > pH > 9.0, NaOA and DEAPA mixed solution form vesicles, thus realizing the regulation of CO2 on the micellar structure transition of NaOA and DEAPA mixed solution. Such these microstructures transition could be confirmed by Rheology measurement, DLS and Cryo-TEM. GRAPHICAL ABSTRACT
The Episodic Prototypes Model (EPM): On the nature and genesis of facial representations

Faces undergo massive changes over time and life events. We need a mental representation which is flexible enough to cope with the existing visual varieties, but which is also stable enough to be the basis for valid recognition. Two main theoretical frameworks exist to describe facial representations: prototype models assuming one central item comprising all visual experiences of a face, and exemplar models assuming single representations of each visual experience of a face. We introduce a much more ecological valid model dealing with episodic prototypes (the Episodic Prototypes Model—EPM), where faces are represented by a low number of prototypes that refer to specific Episodes of Life (EoL, e.g., early adulthood, mature age) during which the facial appearance shows only moderate variation. Such an episodic view of mental representation allows for efficient storage, as the number of needed prototypes is relatively low, and it allows for the needed variation within a prototype that keeps the everyday and steadily ongoing changes across a certain period of time. Studies 1–3 provide evidence that facial representations are highly dependent on temporal aspects which is in accord with EoL, and that individual learning history generates the structure and content of respective prototypes. In Study 4, we used implicit measures (RT) in a face verification task to investigate the postulated power of the EPM. We could demonstrate that episodic prototypes clearly outperformed visual depictions of exhaustive prototypes, supporting the general idea of our approach.
Numerical Simulation of the Effects of Hydrogen Addition to Fuel on the Structure and Soot Formation of a Laminar Axisymmetric Coflow C2H4/(O2-CO2) Diffusion Flame

ABSTRACT Hydrogen is the cleanest energy carrier and has been extensively used as an additive to improve the combustion properties and lower pollutant formation of other hydrocarbons. This numerical study investigated the effects of H2 addition to fuel on the structure and soot formation characteristics of laminar coflow C2H4 diffusion flames burning in an oxidizer stream consisting of 30% O2-70% CO2 at atmospheric pressure using the CoFlame code. Numerical calculations were conducted using a detailed gas-phase reaction mechanism and a soot model comprising the collision of two pyrene molecules as the soot nucleation step, the hydrogen abstraction acetylene addition (HACA) and pyrene condensation as the soot surface growth processes, and soot oxidation by oxygen and OH. Four H2 addition levels of 0, 10, 30, and 50% on volumetric basis were considered. To demonstrate the chemical effects of H2, additional calculations were performed with addition of fictitious hydrogen, FH2. The results confirm the literature finding made in C2H4/air diffusion flames that hydrogen addition to ethylene suppresses soot formation significantly through not only the dilution but also the chemical effects. The effectiveness of H2 on soot formation suppression on per unit percentage addition basis deteriorates as more hydrogen is added to ethylene. The fundamental cause for the reduced soot formation by H2 addition is that the added hydrogen increases the mole fraction of H2, resulting in decreased polycyclic aromatic hydrocarbons (PAHS) concentrations, nucleation rates, and surface growth rates in the soot nucleation and early growth regions. The added H2 to the fuel stream has no chemical interactions with CO2 in the oxidizer stream.
Assessing Chile's Pension System: Challenges and Reform Options

This paper takes stock of Chile’s defined contribution pension system and assesses reform options aimed at increasing replacement rates. An international comparison shows that, despite being quite influential when established, it is now delivering low replacement rates relative to OECD peers, as its parameters did not adapt over time to changing demographics, declining global returns, higher-than-expected informality in the labor market, and, more recently, to legislation allowing for pension savings withdrawals to counter the effects from the COVID-19 pandemic. We find that a reform that raises contribution rates and the retirement age would significantly improve replacement rates and lower fiscal costs associated with the system, especially if accompanied by complementary policies to boost workers’ contribution density. JEL Classification Codes: D14; H30; H55
Statistical Inference for Clustering Results Interpretation in Clinical Practice

The relevance of this study lies in improvement of machine learning models understanding. We present a method for interpreting clustering results and apply it to the case of clinical pathways modeling. This method is based on statistical inference and allows to get the description of the clusters, determining the influence of a particular feature on the difference between them. Based on the proposed approach, it is possible to determine the characteristic features for each cluster. Finally, we compare the method with the Bayesian inference explanation and with the interpretation of medical experts [1].
The Lower Cretaceous carbonate slope-to-platform-margin succession near Khatt, United Arab Emirates: sedimentary facies and depositional geometries

The Jurassic and Lower Cretaceous carbonate succession exposed near Khatt provides exceptional conditions for the investigation of sedimentary facies and depositional geometries in a carbonate slope-to-platform-margin setting. A coarsening-upward sequence in Lower Cretaceous limestones indicates decreasing depth of deposition and platform progradation. A pronounced shedding of sediments containing reefal fragments occurs in a slope environment with a well exposed basin-to-platform transect. The carbonate succession consists of mudstone, wackestone, grainstone, coarse rudstone with conglomerate/breccia interbeds, and framestone at the top. The depositional architecture is characterized by the abundance of massive sheet- or channel-like limestone bodies within thinly bedded and generally uniform strata. Quantitative analysis of many carbonate channel deposits and their geometries measured in outcrop led to the distinction of two major types. Type I channel deposits are thin (0.3 to 5 m) but massive, and are commonly irregularly shaped in cross-section. They are as much as 200 m wide. Type I channel deposits are characterized by a wide size range of skeletal and non-skeletal carbonate components. Type II channel deposits, by contrast, are more regularly bedded and have much larger thickness-to-width ratios, in general close to 1:10. Furthermore, they are composed of packstone to grainstone calciturbidite sediments. As with some sheet deposits, they can be correlated through most of the 5.5-km-long Khatt outcrop. Stratigraphically, however, their occurrence is very much restricted, indicating significant alternation of depositional styles as a consequence of changing carbonate platform production and changing sedimentary environments. The data presented here can serve as input for 3-D geological modeling of equivalent depositional environments in the subsurface. They can also be applied to object-based deterministic and stochastic facies modeling.
Differential Privacy for IoT-Enabled Critical Infrastructure: A Comprehensive Survey

The rapid evolution of the Internet of Things (IoT) paradigm during the last decade has lead to its adoption in critical infrastructure. However, the multitude of benefits that are derived from the IoT paradigm are short-lived due to the exponential rise in the associated security and privacy threats. Adversaries carry out privacy-oriented attacks to gain access to the sensitive and confidential data of critical infrastructure for various self-centered, political and commercial gains. In the past, researchers have employed several privacy preservation approaches including cryptographic encryption and k-anonymity to secure IoT-enabled critical infrastructure. However, for various reasons, those proposed solutions are not well suited for modern IoT-enabled critical infrastructure. Therefore, Dwork’s differential privacy has emerged as the most viable privacy preservation strategy for IoT-enabled critical infrastructure. This paper provides a comprehensive and extensive survey of the application and implementation of differential privacy in four major application domains of IoT-enabled critical infrastructure: Smart Grids (SGs), Intelligent Transport Systems (ITSs), healthcare and medical systems, and Industrial Internet of Things (IIoT). Finally, we discuss some promising future research directions in differential privacy for IoT-enabled critical infrastructure.
Benzene Prediction: A Comparative Study of ANFIS, LSTM and MLR

: It is generally recognized that road traffic emissions are a major health risk and responsible for a substantial share of death and disease in Europe. Although artificial intelligence methods have been used extensively for air pollution forecasting, there is little research on benzene prediction and the use of long short-term memory networks. Benzene is considered one of the pollutants of greatest concern in urban areas and has been linked to leukemia. This paper investigates the predictive power of adaptive neuro-fuzzy inference systems, long short-term memory networks and multiple linear regression models for one hour ahead benzene prediction in the city of Augsburg, Germany. The results of the analysis indicate that adaptive neuro-fuzzy inference systems have the best in sample performance for benzene prediction, whereas long short-term memory networks and multiple linear regressions show similar predictive power. However, long short-term memory models have the best out of sample performance for one hour ahead benzene prediction. This supports the use of long short-term memory networks for benzene prediction in real emission forecasting applications.
Diversity Profiling of Seed Associated Endophytic Microbiome in Important Species of Caricaceae Family

Background: Plant associated endophytic microbes play an important role in plant’s growth and development. After seed germination, the seed associated endophytes rapidly colonize the seedlings and help in their growth and protection against pathogens. This study was aimed to understand the diversity in the endophytic microbial population associated with the seeds of papaya (Carica papaya) and its wild relatives from Vasconcellea genus (family: Caricaceae). The species of Vasconcellea genus are widely used to introgress virus resistance in cultivated varieties of papaya. Hence, the diversity of seed associated endophytic microbes and their gene functional analysis was carried out through next generation sequencing of the microbial 16S rRNA and ITS sequences. Results: The 16S rRNA amplicon analysis revealed that the number of operational taxonomic units (OTUs) was higher for the endophytic bacteria, ranging between 144–204 when compared to 41–69 OTUs for the endophytic fungi. The bacterial phylum Proteobacteria was the most abundant seed associated phylum, with 64.7–72.8% abundance, across all four species of Caricaceae family, followed by Firmicutes (13.6–26.1%), Patescibacteria (1.1–2%) and Actinobacteria (0.7–2.7%). With respect to the diversity of bacteria by abundance indices, Vasconcellea goudotiana had the highest OTUs of 204, followed by 177 in V. cauliflora, 156 in V. cundinamarcensis, and 144 in C. papaya. The alpha diversity indices and functional analysis revealed the differences in the OTUs and the functional annotations among the above four plant species. The fungal OTUs were in the range of 41–69; however, only a small fraction of them could be taxonomically classified. Conclusion: Our microbiome studies reveal the differences in the seed associated endophytic microbial community across the four plant species of Caricaceae family. This study also unravels the composition of endophytic microbial population associated with the seeds of different plant species of Caricaceae family and their gene functions. It also provides an insight into both culturable and nonculturable endophytic microbes. Further this study reveals that domestication of Carica papaya might have resulted into reduced microbial diversity when compared to their wild relatives from Vasconcellea genus.
A new electrically small antenna for on-demand 3.6/5.8 GHz wireless applications

Abstract This article presents a highly miniaturized dual-band electrically small antenna (ESA) for on-demand 3.6 and 5.8 GHz wireless applications. A partial rectangle-shaped structure is printed on the back face of the dielectric material, forming the antenna's ground (GND) plane. The radiating structure of the antenna consists of a C-shaped structure and a U-shaped ring connected to it, which is printed on the dielectric material's front face. The overall dimensions of the designed antenna are 0. 160λo × 0. 160λo × 0. 02λo at the lowest operating frequency. The proposed antenna has a ka value of 0.56 at the lowest operating frequency, which is 3.59 GHz. Thus, the proposed antenna is considered as electrically small. The characteristic mode analysis is adopted to provide a clear understanding of the antenna's resonance behavior. The antenna has been fabricated and the simulation results were validated through measurements. Good agreement between simulated and measured results was obtained. Dual-band operation at 3.62 and 5.75 GHz was achieved, according to the measured reflection coefficient. The proposed antenna offers an adequate performance in terms of gain and efficiency, based on simulation and measurement results. Because of these characteristics, the antenna is well-suited to new wireless applications.
Plasmon‐Induced Pyro‐Phototronic Effect Enhancement in Self‐Powered UV–Vis Detection with a ZnO/CuO p–n Junction Device

It is important to detect light of low power density sensitively and fast for the application of optical communication, environmental monitoring, astronomy, and national securities. However, ZnO‐based photodetectors exhibit long decay time owing to the persistent photoconductivity (PPC) and are hard to detect light with low power density efficiently. Here, a practical strategy is utilized to improve the performance of ZnO‐based photodetectors by coupling the pyroelectric effect of ZnO with localized surface plasmon resonance (LSPR) of Au nanoparticles subtly. Hence, a self‐powered photodetector is demonstrated, which is integrated with ZnO/CuO core–shell nanorods and Au nanoparticles to detect UV to vis light. This self‐powered photodetector achieves fast and sensitive detection of UV when power density is 68 nW cm−2. The performance is significantly improved than the photodetectors without Au nanoparticles. The optimal responsivity and detectivity under the same power density of UV at 325 nm are 1.4 × 10−4 A W−1 and 3.3 × 1011 Jones. Response/recovery time is remarkably shortened to ≈10 ms. The results indicate that the material configurations and design concept make the device applicable for self‐powered, high‐performance photodetectors, and provide further promoted understanding of LSPR enhanced performance of photodetectors.
Assessing Athletic Motor Skill Competencies in Youths: A Narrative Review of Movement Competency Screens

ABSTRACT Leading health organizations and long-term athletic development models have identified the need to develop movement competencies in children and adolescents. The athletic motor skill competencies (AMSCs) have been identified as key skills that form the foundations of all athletic movements. The AMSCs form an integral part of the long-term athletic development of youth, and improving these qualities should be central to coaches working with young individuals. Multiple movement competency screens assess some aspects of the AMSC spectrum, but there is no consensus regarding which screens may be most appropriate for a given cohort or coaching environment. This review provides an evaluation of the movement screens available to assess various AMSCs and in turn considers their reliability, feasibility, strengths, and weaknesses when used with youth populations.