bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ressentimentale Politik
Authors: Rösch Viktoria 
Published: June 2022

ZusammenfassungIn diesem Beitrag wird politische Kommunikation in den Sozialen Medien aus dem Blickwinkel der Gefühlsarbeit analysiert. Die Etablierung mobilisierender Narrative wird als Verschränkung von konkreten Ereignissen, kollektiven Wissensbeständen und Affektproduktionen verstanden. Die Rekonstruktion der medialen Praxis erfolgt anhand der Analyse eines YouTube-Videos einer rechten Fraueninitiative zur Kölner Silvesternacht. Dafür werden Mechanismen des Ethnosexismus skizziert und deren affektive Grundierung ausgeleuchtet. Nach der Darstellung des empirischen Falls wird das methodische Vorgehen, angelehnt an den Vorschlag einer Audiovisuellen Grounded Theory Methodologie (AVGTM), vorgestellt. Als Schlüsselkategorie wird die Arbeit an und mit dem ‚ethnosexistischen Ressentiment‘ herausgearbeitet.
Antidepressant alkaloids from the rhizomes of Corydalis decumbens
Authors: Ma Qin-Ge , Tang Ye , He Mao-Hua , Wei Rong-Rui 
Published: June 2022

Abstract
Two new alkaloids (1 and 2), named 1,7-dimethoxy-2′-prenyl-1′,9-dihydropyrrolo-carbazole (1) and 1,7-dimethoxy-4′,5′-dimethylcyclopenta-carbazole-1′,3′-dione (2), along with thirteen known alkaloids (3–15) were isolated by means of silica gel, sephadex LH-20, and semi-preparative HPLC from the CHCl3 extraction of Corydalis decumbens for the first time. Their structures were determined by NMR, MS, IR, UV, and related references. Compounds (1–15) were evaluated for their antidepressant activities by measuring inhibition of monoamine neurotransmitter reuptake in vitro. Among them, compounds 1, 2, 4, and 6 showed certain antidepressant activities.
PENGHAYATAN WARGANEGARA MALAYSIA TERHADAP LAMBANG KENEGARAAN MALAYSIA DAN CABARAN REVOLUSI PERINDUSTRIAN 4.0: SATU PENELITIAN AWAL
Authors: HANIFFA MOHAMED ALI , Ayu Nor Azilah Mohamad  
Published: June 2022

Abstract - This article discusses the Malaysian community's appreciation of the Malaysian Nationhood symbols. The Malaysian Nationhood symbols include the National Coat of Arms, National Anthem, National Flag, National Language and National Flower. It also discusses the readiness of Malaysian citizens in facing the challenges of the Industrial Revolution 4.0. This article is a preliminary study based on literature highlights, readings, inquiries and views. This study used library resources including circulars, books, journals and websites. The results of the study based on the preliminary survey showed that the awareness and sensitivity of the Malaysian community in cultivating identity and patriotism towards the country can still be improved.

Abstrak - Artikel ini membincangkan mengenai penghayatan masyarakat Malaysia terhadap lambang Kenegaraan Malaysia. Lambang Kenegaraan Malaysia meliputi Jata Negara, Lagu Kebangsaan, Bendera Kebangsaan, Bahasa Kebangsaan dan Bunga Kebangsaan. Turut dibincangkan ialah persediaan yang diperlu dilakukan oleh warganegara Malaysia dalam mendepani cabaran Revolusi Industri 4.0. Artikel ini merupakan penelitian awal berdasarkan kepada sorotan literatur, pembacaan, penelitian dan pandangan. Kajian ini menggunakan sumber perpustakaan meliputi Pekeliling, buku, jurnal dan laman sesawang. Hasil kajian berdasarkan tinjauan awal menunjukkan bahawa kepekaan dan sensitiviti masyarakat Malaysia masih boleh dipertingkatkan dalam memupuk jati diri dan patriotisme terhadap negara.
Keberadaan Hasil Kali Langsung dari Ruang Bernorma
Authors: Agustito Denik , Kuncoro Krida Singgih , Irfan Muhammad 
Published: June 2022

Keberadaan hasil kali langsung tidak selalu ada dalam sebuah kategori. Pada kategori dari ruang vektor bersama dengan transfomarsi linear (operator linear) memiliki hasil kali langsung berhingga maupun tak-hingga; artinya kategori tersebut tertutup di bawah hasil kali langsung berhingga maupun tak-berhingga, tetapi dalam kategori ruang bernorma bersama dengan operator linear terbatasnya tidak memiliki hasil kali langsung tak-berhingga namun hanya memiliki hasil kali langsung berhingga saja; artinya kategori tersebut tertutup di bawah hasil kali langsung berhingga saja dan tidak untuk hasil kali langsung tak-hingga. Sebagai akibat keberadaan hasil kali langsung berhingga dari ruang bernorma adalah adalah ruang banach jika dan hanya jika E1, ..., En juga merupakan ruang banach.
Validation of Prediction Models for Pneumonia Among Children in the Emergency Department
Authors: Ramgopal Sriram , Lorenz Douglas , Navanandan Nidhya , Cotter Jillian M. , Shah Samir S. , Ruddy Richard M. , Ambroggio Lilliam , Florin Todd A. 
Published: June 2022

BACKGROUND
Several prediction models have been reported to identify patients with radiographic pneumonia, but none have been validated or broadly implemented into practice. We evaluated 5 prediction models for radiographic pneumonia in children.

METHODS
We evaluated 5 previously published prediction models for radiographic pneumonia (Neuman, Oostenbrink, Lynch, Mahabee-Gittens, and Lipsett) using data from a single-center prospective study of patients 3 months to 18 years with signs of lower respiratory tract infection. Our outcome was radiographic pneumonia. We compared each model’s area under the receiver operating characteristic curve (AUROC) and evaluated their diagnostic accuracy at statistically-derived cutpoints.

RESULTS
Radiographic pneumonia was identified in 253 (22.2%) of 1142 patients. When using model coefficients derived from the study dataset, AUROC ranged from 0.58 (95% confidence interval, 0.52–0.64) to 0.79 (95% confidence interval, 0.75–0.82). When using coefficients derived from original study models, 2 studies demonstrated an AUROC &gt;0.70 (Neuman and Lipsett); this increased to 3 after deriving regression coefficients from the study cohort (Neuman, Lipsett, and Oostenbrink). Two models required historical and clinical data (Neuman and Lipsett), and the third additionally required C-reactive protein (Oostenbrink). At a statistically derived cutpoint of predicted risk from each model, sensitivity ranged from 51.2% to 70.4%, specificity 49.9% to 87.5%, positive predictive value 16.1% to 54.4%, and negative predictive value 83.9% to 90.7%.

CONCLUSIONS
Prediction models for radiographic pneumonia had varying performance. The 3 models with higher performance may facilitate clinical management by predicting the risk of radiographic pneumonia among children with lower respiratory tract infection.
Nutrient and Trace Element Contributions from Drained Islands in the Sacramento–San Joaquin Delta, California
Authors:   University of California, Santa Cruz, Richardson Christina , Fackrell Joseph ,   University of California, Santa Cruz, Kraus Tamara E. C. ,   US Geological Survey, Young Megan ,   US Geological Survey, Paytan Adina ,   University of California, Santa Cruz
Published: June 2022

Inventorying nutrient and trace element sources in the Sacramento-San Joaquin Delta (the Delta) is critical to understanding how changes—including alterations to point source inputs such as upgrades to the Sacramento Regional Wastewater Treatment Plant (SRWTP) and landscape-scale changes related to wetland restoration—may alter the Delta’s water quality. While island drains are a ubiquitous feature of the Delta, limited data exist to evaluate island drainage mass fluxes in this system. To better constrain inputs from island drains, we measured monthly discharge along with nutrient and trace element concentrations in island drainage on three Delta islands and surrounding rivers from June 2017 to September 2018. These data were used to calculate island-level fluxes and then upscaled to estimate Delta-wide contributions from island drains. Based on these results, we present (1) new estimates of gross and net nutrient and trace element fluxes from Delta island drains, and (2) concomitant N stable isotope data to improve our understanding of island N cycling. Over 60% of nearly all island drainage gross nutrient and trace element loads occurred in winter and spring. Upscaled island drainage net annual total nitrogen (TN), total dissolved nitrogen (TDN), and NH4+ loads comprised an estimated 9%, 7%, and 4%, respectively, of annual inputs to this system in 2018, before the SRWTP upgrade. Under a post-upgrade scenario, we estimated net annual island drainage TDN contributions to increase to 11% and NH4+ contributions to 45% of total Delta inputs as the SRWTP NH4+ load diminished to near zero. Our results suggest that island drainage is a measurable N source that has likely become increasingly important now that the SRWTP upgrade is complete. With over 200 potential active outfalls, these inputs may affect aquatic biogeochemical cycling in many regions of the Delta, especially in areas with long residence times.
Development and application of hybrid artificial intelligence models for groundwater potential mapping and assessment
Authors: Hai Ha Duong , Thi Thanh Ngo Huong , Tran Van Phong , Nguyen Duc Dam , Avand Mohammadtaghi , Nguyen Huu Duy , Amiri Mahdis , Van Le Hiep , Prakash Indra , Binh Thai Pham 
Published: June 2022

Groundwater potential assessment is essential for optimum utilization and recharge of groundwater resources for the proper development and management of an area. The main aim of this study is to develop an accurate groundwater potential map of the Dak Nong Province (Vietnam) using hybrid artificial intelligence models, which are a combination of Random Forest (RF) and its Ensemble Framework (AdaBoost - ABRF, Bagging - BRF and LogitBoost - LBRF). In this study, twelve conditioning factors, namely topography (aspect, elevation, Topographic Wetness Index - TWI, slope, and curvature), hydrology (infiltration and river density, rainfall, Sediment Transport Index - STI, Stream Power Index - SPI), land use, and soil were used to develop the models. Well, yield data was also utilized to develop and validate potential groundwater zones.
One Rule (R) feature selection method was utilized to prioritize the importance of groundwater potential affecting parameters. The results indicated that the Average Merit (AM) of the rainfall factor was the highest (68.039), and river density was the lowest (53,969). Performance evaluation of ML models was done using standard statistical indicators, including Area Under the Receiver Operating Characteristic (ROC) curve (AUC). The results showed that all the four models performed well in the training (AUC ≥ 0.967) and testing (AUC ≥ 0.734) phases, but the performance of the ABRF (AUC=0.992) model is the best in the training phase, whereas LBRF is the best in the testing phase (AUC=0.776). The present model study would be helpful in the proper groundwater potential assessment and management of groundwater resources for sustainable development.
Extensive-Form Perfect Equilibrium Computation in Two-Player Games
Authors: Farina Gabriele , Gatti Nicola 
Published: June 2022

We study the problem of computing an Extensive-Form Perfect Equilibrium (EFPE) in 2-player games. This equilibrium concept refines the Nash equilibrium requiring resilience with respect to a specific vanishing perturbation, representing mistakes of the players at each decision node. The scientific challenge is intrinsic to the EFPE definition: it requires a perturbation over the agent form, but the agent form is computationally inefficient due to the presence of highly nonlinear constraints. We show that the sequence form can be exploited in a non-trivial way and that, for general-sum games, finding an EFPE is equivalent to solving a suitably perturbed linear complementarity problem. We prove that Lemke's algorithm can be applied, showing that computing an EFPE is PPAD-complete. In the notable case of zero-sum games, the problem is in FP and can be solved by linear programming. Our algorithms also allow one to find a Nash equilibrium when players cannot perfectly control their moves, being subject to a given execution uncertainty, as is the case in most realistic physical settings.
Randomized Mechanisms for Selling Reserved Instances in Cloud
Authors: Zhang Jia , Ma Weidong , Qin Tao , Sun Xiaoming , Liu Tie-Yan 
Published: June 2022

Selling reserved instances (or virtual machines) is a basic service in cloud computing. In this paper, we consider a more flexible pricing model for instance reservation, in which a customer can propose the time length and number of resources of her request, while in today's industry, customers can only choose from several predefined reservation packages. Under this model, we design randomized mechanisms for customers coming online to optimize social welfare and providers' revenue. We first consider a simple case, where the requests from the customers do not vary too much in terms of both length and value density. We design a randomized mechanism that achieves a competitive ratio 1/42 for both social welfare and revenue, which is a improvement as there is usually no revenue guarantee in previous works such as (Azar et al. 2015; Wang et al. 2015. This ratio can be improved up to 1/11 when we impose a realistic constraint on the maximum number of resources used by each request. On the hardness side, we show an upper bound 1/3 on competitive ratio for any randomized mechanism.We then extend our mechanism to the general case and achieve a competitive ratio 1/42⌈log k⌉ log T for both social welfare and revenue, where T is the ratio of the maximum request length to the minimum request length and k is the ratio of the maximum request value density to the minimum request value density. This result outperforms the previous upper bound 1/CkT for deterministic mechanisms (Wang et al. 2015). We also prove an upper bound 2/log 8kT for any randomized mechanism. All the mechanisms we provide are in a greedy style. They are truthful and easy to be integrated into practical cloud systems.
A General Framework for Sparsity Regularized Feature Selection via Iteratively Reweighted Least Square Minimization
Authors: Peng Hanyang , Fan Yong 
Published: June 2022

A variety of feature selection methods based on sparsity regularization have been developed with different loss functions and sparse regularization functions. Capitalizing on the existing sparsity regularized feature selection methods, we propose a general sparsity feature selection (GSR-FS) algorithm that optimizes a ℓ2,r (0 < r ≤ 2) based loss function with a ℓ2,p-norm (0 < p ≤ 2) sparse regularization. The ℓ2,r-norm (0 <
The Opacity of Backbones
Authors: Hemaspaandra Lane , Narváez David 
Published: June 2022

A backbone of a boolean formula F is a collection S of its variables for which there is a unique partial assignment aS such that F[aS] is satisfiable (Monasson et al. 1999; Williams, Gomes, and Selman 2003). This paper studies the nontransparency of backbones. We show that, under the widely believed assumption that integer factoring is hard, there exist sets of boolean formulas that have obvious, nontrivial backbones yet finding the values, aS, of those backbones is intractable. We also show that, under the same assumption, there exist sets of boolean formulas that obviously have large backbones yet producing such a backbone S is intractable. Further, we show that if integer factoring is not merely worst-case hard but is frequently hard, as is widely believed, then the frequency of hardness in our two results is not too much less than that frequency.
Manipulative Elicitation — A New Attack on Elections with Incomplete Preferences
Authors: Dey Palash 
Published: June 2022

Lu and Boutilier proposed a novel approach based on "minimax regret" to use classical score based voting rules in the setting where preferences can be any partial (instead of complete) orders over the set of alternatives. We show here that such an approach is vulnerable to a new kind of manipulation which was not present in the classical (where preferences are complete orders) world of voting. We call this attack "manipulative elicitation." More specifically, it may be possible to (partially) elicit the preferences of the agents in a way that makes some distinguished alternative win the election who may not be a winner if we elicit every preference completely. More alarmingly, we show that the related computational task is polynomial time solvable for a large class of voting rules which includes all scoring rules, maximin, Copeland α for every α ∈ [0,1], simplified Bucklin voting rules, etc. We then show that introducing a parameter per pair of alternatives which specifies the minimum number of partial preferences where this pair of alternatives must be comparable makes the related computational task of manipulative elicitation NP-complete for all common voting rules including a class of scoring rules which includes the plurality, k-approval, k-veto, veto, and Borda voting rules, maximin, Copeland α for every α ∈ [0,1], and simplified Bucklin voting rules. Hence, in this work, we discover a fundamental vulnerability in using minimax regret based approach in partial preferential setting and propose a novel way to tackle it.
On Convergence of Epanechnikov Mean Shift
Authors: Huang Kejun , Fu Xiao , Sidiropoulos Nicholas 
Published: June 2022

Epanechnikov Mean Shift is a simple yet empirically very effective algorithm for clustering. It localizes the centroids of data clusters via estimating modes of the probability distribution that generates the data points, using the "optimal" Epanechnikov kernel density estimator. However, since the procedure involves non-smooth kernel density functions,the convergence behavior of Epanechnikov mean shift lacks theoretical support as of this writing---most of the existing analyses are based on smooth functions and thus cannot be applied to Epanechnikov Mean Shift. In this work, we first show that the original Epanechnikov Mean Shift may indeed terminate at a non-critical point, due to the non-smoothness nature. Based on our analysis, we propose a simple remedy to fix it. The modified Epanechnikov Mean Shift is guaranteed to terminate at a local maximum of the estimated density, which corresponds to a cluster centroid, within a inite number of iterations. We also propose a way to avoid running the Mean Shift iterates from every data point, while maintaining good clustering accuracies under non-overlapping spherical Gaussian mixture models. This further pushes Epanechnikov Mean Shift to handle very large and high-dimensional data sets. Experiments show surprisingly good performance compared to the Lloyd's K-means algorithm and the EM algorithm.
Universidad en contexto - Editorial
Authors: Sánchez-Cabrera Samuel Alberto 
Published: June 2022

La situación actual demanda retos significativos para la Universidad, toda vez que, se muestra la importancia de las instituciones de educación, las cuales son fundamentales para la sociedad a partir de las respuestas a los problemas sentidos, tales como los originados por la pandemia, los de orden económico y la confianza social. De tal manera que, la Universidad se manifiesta no solo como un espacio físico, sino en un concepto más amplio donde los miembros de la comunidad académica interactúan con los actores nucleares de la sociedad para dar respuesta adecuadas a problemas de orden regional y nacional. Se reclama oportunidades de empleo, mayor educación y de calidad y es aquí donde la articulación del estado, la universidad y la empresa es imprescindible.
Strategic Vectors for Enterprise Development in the Context of the Digitalization of the Economy
Authors: Kibik Olha , Taran-Lala Olena , Saienko Volodymyr , Metil Tetiana , Umanets Tetiana , Maksymchuk Iryna 
Published: June 2022

In the realities of the digital economy there are fast and permanent processes of digitalization of economic relations and economic activity, technologies, information and knowledge in the field of business management are becoming increasingly important. Modern economic conditions in which enterprises operate are characterized by globality, dynamism and uncertainty. One of the main factors that can ensure the company's stability in the market and help strengthen its position is a well-founded development strategy.
Depending on the direction of enterprise development, it is important to distinguish such strategies as intensification, integration and diversification, which can be applied individually or in combination. The need to adapt to the conditions of comprehensive digitalization requires enterprises to take an innovative approach to their activities, and the harmonization of the mechanism of strategic management of innovative development of the enterprise should consist of determining the vector of innovative transformations. Knowledge is very important in the innovation process, because it is not only an important contribution, but also the result of the process of transformation of innovation culture of enterprises.
The use of modern methods of e-commerce, digital platforms and blockchain allows companies to gain new benefits and opportunities. Enterprises that choose as a strategic vector of development a systematic combination of innovative approach to their activities, analysis of internal and external resources of development, adequate adaptation to the external realities of the digital economy, achieve high results in the present and future.
Psychological features of Russia’s media image
Authors: Sveshnikova Natalia , Volynskaia Maria 
Published: June 2022

In the recent years in the field of theoretical and practical scientific knowledge the quality aspects of information have been highlighted as having the most influence on the audience. In that regard the most attention is being given to discourse representation; its role in social constructing is being thoroughly analysed. Studies of media discourse are conducted in terms of interdisciplinary approach. The main aim of our research is to identify psychological contents of Russia’s representation in Russian federal print mass media. We developed a 3-stage method which is a modification of content analysis method. Our research showed the possibility of psychological analysis of the discourse representation’s direction onto reflection/construction. The conducted analysis allowed us to identify structural characteristics of Russia’s media image and to describe their dynamics. We outlined the specifics of information presentation which may define the pattern of influence on the audience. The research illustrates the possibilities of conducting comparative analysis of media images of different countries.

Keywords: Media Image; Russia; Discourse; Psychological Influence; Representation;