Estimating the Psychological Impact of Mass Shooting and Terrorist Attacks on Remote Populations

Most research examining the psychological impact of public mass-shootings and terrorist attacks focuses on the immediate victims (i.e., those at/near the scene of the crime or living nearby). Research consistently demonstrates that these directly targeted individuals experience a wide-array of adverse mental health outcomes following these traumatic events (Lowe & Galea, 2017; Wilson, 2014). What remains less understood, however, is how these violent episodes afflict the broader public who are exposed to the trauma largely through indirect means, such as media and word of mouth. While prior scholarship in this area remains quite limited, it also tends to suffer from several methodological limitations (e.g., cross sectional research design or case-study analysis of singular events). To address these limitations, this study employed a Time Series Cross Sectional (TSCS) framework, enabling an estimation of the impact of mass shooting and terrorist attacks on the general public across 72 deadly events during a 6-year period (2012-2017). In addition, this study involved an empirical testing of dose-response theory (APA, 1980), utilizing characteristics of each event (casualty rates and level of media exposure) as proxy measures for trauma dosage. Overall, findings from this study indicate that remotely exposed communities are not seriously affected psychologically by these incidents. Research and policy implications for public health and media reporting are discussed

Determinants of Market Participation and Intensity of Participation of Teff Producers in West Arsi Zone of Oromia, Ethiopia

In Ethiopia, agricultural transformation is taken as a pathway to transition from a traditional subsistence orientation to market focused and commercialized farming system. In this regard, efforts to enhance smallholders’ participation in cereal market in general and teff in particular have made through boosting production . Nevertheless there is dearth of information on the teff of market participation and its intensity of participation in central Oromia particularly in Shashamane district. Therefore, this study was analyzed market participation and extent of teff market participation of farmers. The total 202 respondents were selected by using two stage sampling techniques and also interviewed. Double hurdle model was used to identify the determinants of market participation decisions and extent of market participation. The study showed that, educational level, livestock owned, land allocation for teff production, extension contact had positive significant effect on teff market participation decision, while sex of household head, family size, distance to nearest market had significant and negative effect. Intensity of market participation was affected positively and significantly by land allocated for teff, while family size and non-farm income significantly and negatively affect level of teff mark supply Therefore, focus on strengthening the technical, resource base, infrastructural and institutional capacity building of smallholder farmers are strategies that promote teff producers market participation and Intensity of participation. Keywords: Double hurdle model, Smallholder farmers, Teff market participation DOI: 10.7176/FSQM/101-04 Publication date:September 30th 2020

Content an Insight to Security Paradigm for BigData on Cloud: Current Trend and Research

The sucesssive growth of collabrative applications prodcuing Bigdata on timeline leads new opprutinity to setup commodities on cloud infrastructure. Mnay organizations will have demand of an efficient data storage mechanism and also the efficient data analysis. The Big Data (BD) also faces some of the security issues for the important data or information which is shared or transferred over the cloud. These issues include the tampering, losing control over the data, etc. This survey work offers some of the interesting, important aspects of big data including the high security and privacy issue. In this, the survey of existing research works for the preservation of privacy and security mechanism and also the existing tools for it are stated. The discussions for upcoming tools which are needed to be focused on performance improvement are discussed. With the survey analysis, a research gap is illustrated, and a future research idea is presente

Methodological guidelines for the design, implementation and assessment of Digital Action

This report aims to create the conditions for the co-creation of Digital Action between citizens, HE staff and students. It is intended as the basis for a set of methodological guidelines for the design, implementation and assessment of digital activities by High Education Institutions. All the information is based on existing guidelines and insights on the barriers and drivers of Digital Action

A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction

Machine learning models are gaining increasing popularity in the domain of fluid dynamics for their potential to accelerate the production of high-fidelity computational fluid dynamics data. However, many recently proposed machine learning models for high-fidelity data reconstruction require low-fidelity data for model training. Such requirement restrains the application performance of these models, since their data reconstruction accuracy would drop significantly if the low-fidelity input data used in model test has a large deviation from the training data. To overcome this restraint, we propose a diffusion model which only uses high-fidelity data at training. With different configurations, our model is able to reconstruct high-fidelity data from either a regular low-fidelity sample or a sparsely measured sample, and is also able to gain an accuracy increase by using physics-informed conditioning information from a known partial differential equation when that is available. Experimental results demonstrate that our model can produce accurate reconstruction results for 2d turbulent flows based on different input sources without retraining

Inpainting Computational Fluid Dynamics with Deep Learning

Fluid data completion is a research problem with high potential benefit for both experimental and computational fluid dynamics. An effective fluid data completion method reduces the required number of sensors in a fluid dynamics experiment, and allows a coarser and more adaptive mesh for a Computational Fluid Dynamics (CFD) simulation. However, the ill-posed nature of the fluid data completion problem makes it prohibitively difficult to obtain a theoretical solution and presents high numerical uncertainty and instability for a data-driven approach (e.g., a neural network model). To address these challenges, we leverage recent advancements in computer vision, employing the vector quantization technique to map both complete and incomplete fluid data spaces onto discrete-valued lower-dimensional representations via a two-stage learning procedure. We demonstrated the effectiveness of our approach on Kolmogorov flow data (Reynolds number: 1000) occluded by masks of different size and arrangement. Experimental results show that our proposed model consistently outperforms benchmark models under different occlusion settings in terms of point-wise reconstruction accuracy as well as turbulent energy spectrum and vorticity distribution.Comment: 20 pages, 9 figure

Scalable Transformer for PDE Surrogate Modeling

Transformer has shown state-of-the-art performance on various applications and has recently emerged as a promising tool for surrogate modeling of partial differential equations (PDEs). Despite the introduction of linear-complexity variant, applying attention to a large number of grid points can result in instability and is still expensive to compute. In this work, we propose Factorized Transformer(FactFormer), which is based on an axial factorized kernel integral. Concretely, we introduce a learnable projection operator that decomposes the input function into multiple sub-functions with one-dimensional domain. These sub-functions are then evaluated and used to compute the instance-based kernel with an axial factorized scheme. We showcase that the proposed model is able to simulate 2D Kolmogorov flow on a 256 by 256 grid and 3D smoke buoyancy on a 64 by 64 by 64 grid with good accuracy and efficiency. In addition, we find out that with the factorization scheme, the attention matrices enjoy a more compact spectrum than full softmax-free attention matrices

PENERAPAN MODEL PEMBELAJARAN SNOWBALL THROWING UNTUK PENINGKATAN HASIL BELAJAR SISWA PADA MATA PELAJARAN DASAR LISTRIK DAN ELEKTRONIKA DI KELAS X TEKNIK AUDIO VIDEO SMK NEGERI 2 KUPANG

Penelitian ini merupakan jenis penelitian tindakan kelas, dengan model pembelajaran yang diterapkan adalah model pembelajaran kooperatif tipe Snowball Throwing. Sedangkan variabel yang diukur adalah hasil belajar siswa. Teknik pengumpulan data dalam penelitian ini menggunakan lembar observasi, tes dan dokumentasi. Analisis data dilakukan dengan analisis deskriptif kualitatif Penerapan model pembelajaran Snowball Throwing terbukti dapat meningkatkan hasil belajar siswa kelas X Teknik Audio Video SMK Negeri2 Kupang pada mata pelajaran dasar listrik dan elektronika. Hal tersebut dapat dilihat pada pre test terdapat 7 orang siswa (23,33%) yang memperoleh skor 75 ke atas dengan nilai rata-rata 53,33%, tes siklus I terdapat 17 orang siswa (56,66%) yang memperoleh skor 75 ke atas dengan nilai rata-rata 73,66% dan tes siklus II terdapat 30 orang siswa (100%) yang memperoleh skor 75 ke atas dengan nilai rata-rata 85,33%

FORMULATION DEVELOPMENT OF MOUTH DISSOLVING PRINTED FILM OF KETOROLAC AND IN VITRO EVALUATION

Objective: The present research work was carried out to prepare Ketorolac printed Oral Thin Films using a pneumatic pressure printer. In this research, we attempted to prepare a non-contact printing system by using pneumatic pressure-based printer that incorporates printing of active pharmaceutical ingredients onto a medical-grade Orodispersible film for developing personalized medication. Methods: In the present work Ketorolac Trometamol was used as a model drug. Placebo substrate was developed by using cellulosic polymers like HPMC, MCC, Neusilin, and starch to impart paper-like properties that are desirable for printing. It was evaluated for various physicochemical properties like disintegration time, mechanical strength, folding endurance, surface properties, etc. Polymers and plasticizers were evaluated for the development of drug loaded Printing ink. The drug-printed films were characterized for physicochemical properties and in vitro drug dissolution. Results: Various film-forming polymers were evaluated for the development of printing substrates. The F3 substrate had desired mechanical properties i.e. the thickness of 0.157±0.003, the tensile strength of 0.331±0.016, disintegration within 60 seconds, and this substrate also maintained its integrity after the printing of the drug ink. The HPMC-based ink (I4) with polyethylene glycol for modulating flow properties of ink in the concentration of 1.40%w/v was selected among various ink formulations. The drug release from the printed films was 98±1.94% in 1 h. Conclusion: Through this new drug printing technology the limitation of low drug dose loading associated with ink-jet and flexographic printing can be solved by increasing the drug loading ranges from micrograms to milligrams by a single pass of the print head

PENGGUNAAN AUKSIN ALAMI SEBAGAI ZAT PENGATUR TUMBUH (ZPT) TERHADAPPERTUMBUHAN STEK BIBIT JAMBU AIR (Syszygium samarangense)

       Use of Natural Auksin as Growth Zat (ZPT) Against Growth of Stam Breeding Water Jamboo (Syszygium samarangense).This study aims to determine the effect of the use of auksin extract of onion, garlic extract and onion extract as well as the effect of the best extract on the growth of water cashew cuttings (Syzygium samarangense)The study was arranged by Randomized Block Design with single factor pattern consisting of four treatments ie without auxin (A-0), auksin extract of onion (A-1), auksin garlic extract (A-2) and auksin garlic extract bombai (A-3). The observation variables in this study were: percentage of live cuttings (%), root length (cm), root quantity, fresh root weight (g), fresh weight weight (g), dry root weight (g) and dry weight weight (g)The results showed the use of axin onion extract 90%, can increase the percentage of live cuttings (2.99%), root length (51.22%); number of roots (56.55%), fresh root weight (47.54%); weight of fresh stover (26.22%); dry root weight (51.72%) and weight of dry stover (27.64%). The use of 90% onion extract gave the best influence to the growth of root cashew cuttings which resulted in live cuttings percentage (98.86%); root length (10.04 cm); number of roots (19,20); fresh root weight (2.02 g); fresh fresh weight (17.22 g); dry weight of roots (1.06 g) and weight of dry stover (8.60 g)