bluuebunny/crossref_metadata_2025_split huggingface dataset:
Retrospection of heatwave and heat index
Authors: Awasthi Amit , Vishwakarma Kirti , Pattnayak Kanhu Charan 
Published: November 2021

AbstractThe frequency and intensity of extreme events especially heat waves (HW) are growing all around the world which ultimately poses a serious threat to the health of individuals. To quantify the effects of extreme temperature, appropriate information, and the importance of HW and heat index (HI) are carefully discussed for different parts of the world. Varied definitions of the HW and HI formula proposed and used by different countries are carried out systematically continent-wise. Different studies highlighted the number of definitions of HW; however, mostly used Steadman’s formulae, which was developed in the late 1970s, for the calculation of HI that uses surface air temperature and relative humidity as climatic fields. Since then, dramatic changes in climatic conditions have been observed as evident from the ERA5 datasets which need to be addressed; likewise, the definition of HW, which is modified by the researchers as per the geographic conditions. It is evident from the ERA5 data that the temperature has increased by 1–2 °C as compared to the 1980s. There is a threefold increase in the number of heatwave days over most of the continents in the last 40 years. This study will help the researcher community to understand the importance of HW and HI. Furthermore, it opens the scope to develop an equation based on the present scenario keeping in mind the basics of an index as considered by Steadman.
Inexact accelerated high-order proximal-point methods
Authors: Nesterov Yurii 
Published: November 2021

AbstractIn this paper, we present a new framework ofbi-level unconstrained minimizationfor development of accelerated methods in Convex Programming. These methods use approximations of the high-order proximal points, which are solutions of some auxiliary parametric optimization problems. For computing these points, we can use different methods, and, in particular, the lower-order schemes. This opens a possibility for the latter methods to overpass traditional limits of the Complexity Theory. As an example, we obtain a new second-order method with the convergence rate$$O\left( k^{-4}\right) $$Ok-4, wherekis the iteration counter. This rate is better than the maximal possible rate of convergence for this type of methods, as applied to functions with Lipschitz continuous Hessian. We also present new methods with the exact auxiliary search procedure, which have the rate of convergence$$O\left( k^{-(3p+1)/ 2}\right) $$Ok-(3p+1)/2, where$$p \ge 1$$p≥1is the order of the proximal operator. The auxiliary problem at each iteration of these schemes is convex.
Blockchain drivers to achieve sustainable food security in the Indian context
Authors: Yadav Vinay Surendra , Singh A. R. , Raut Rakesh D. , Cheikhrouhou Naoufel 
Published: November 2021

AbstractBlockchain has the potential to improve sustainable food security due to its unique features like traceability, decentralized and immutable database, and smart contract mechanisms. However, blockchain technology is still in the early stages of adoption in particular in agricultural applications. In this context, this article aims to identify blockchain drivers to achieve sustainable food security in the Indian context and model them using an integrated MCDM (Multiple Criteria Decision Making) approach. The blockchain adoption drivers are identified through an exhaustive literature review and opinions from domain experts from industry, academia, and Agriculture Supply Chain (ASC) stakeholders. Subsequently, the integrated MCDM approach is developed by combining Total Interpretive Structural Modelling (TISM) and Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), which does not only investigate the interrelation between the identified constructs and builds hierarchy but also determines the intensity of the causal interrelationships. At a later stage, Fuzzy Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) is used to cluster the identified drivers to evaluate the importance of each driver. The results reveal that Traceability, Real-time information availability to agro-stakeholder, and Decentralized and immutable database are the most significant drivers. Policymakers, governmental organizations and other relevant stakeholders may utilize the information about the interrelationship between these drivers and their influential power, to frame suitable strategies for enhancing the adoption rate of blockchain in the Indian ASC.
Hazard-consistent seismic losses and collapse capacities for light-frame wood buildings in California and Cascadia
Authors: Chase Robert E. , Liel Abbie B. , Luco Nicolas , Bullock Zach 
Published: November 2021

AbstractWe evaluate the seismic performance of modern seismically designed wood light-frame (WLF) buildings, considering regional seismic hazard characteristics that influence ground motion duration and frequency content and, thus, seismic risk. Results show that WLF building response correlates strongly with ground motion spectral shape but weakly with duration. Due to the flatter spectral shape of ground motions from subduction events, WLF buildings at sites affected by these earthquakes may experience double the economic losses for a given intensity of shaking, and collapse capacities may be reduced by up to 50%, compared to those at sites affected by crustal earthquakes. These differences could motivate significant increases in design values at sites affected by subduction earthquakes to achieve the uniform risk targets of the American Society of Civil Engineers (ASCE) 7 standard.
Kann der ASD Kinder- und Jugendstärkungsgesetz?
Authors: Pietsch Stefan , Klomann Verena 
Published: November 2021

ZusammenfassungZahlreiche Neuerungen der SGB VIII-Reform wirken sich auf die Arbeit im ASD des Jugendamtes aus. Gleichzeitig wird deren Umsetzung maßgeblich durch den ASD beeinflusst. Exemplarisch werden hiermit einhergehende An- und Herausforderungen aus ASD-Perspektive diskutiert und Entwicklungsimpulse aufgezeigt.
Heart rate increase and inappropriate sinus tachycardia after cryoballoon pulmonary vein isolation for atrial fibrillation
Authors: van Deutekom C. , Mulder B. A. , Groenveld H. F. , Tieleman R. G. , Wiesfeld A. C. P. , Tan E. S. , van Gelder I. C. , Rienstra M. , Blaauw Y. 
Published: November 2021

Abstract
Background
Cryoballoon pulmonary vein isolation (PVI) is a common therapy for atrial fibrillation (AF). While moderately increased sinus rhythm heart rate (HR) after PVI has been observed, inappropriate sinus tachycardia (IST) is a rare phenomenon. We aimed to investigate the prevalence and natural history of an abnormal sinus HR response after cryoballoon PVI.

Methods
We included 169/646 (26.2%) patients with AF undergoing PVI with available Holter recordings before and 3, 6 and 12 months after the procedure. Patients with AF on Holter monitoring were excluded. Mean HR increase ≥ 20 bpm or an IST-like pattern (mean HR > 90 bpm or > 80 bpm when beta-blocking agents were used) following PVI was categorised as abnormal sinus HR response.

Results
Following PVI, mean HR ± standard deviation increased in the entire group from 63.5 ± 8.4 to 69.1 ± 9.9 bpm at 3 months (p < 0.001), and to 71.9 ± 9.4 bpm at 6 months (p < 0.001). At 12 months, mean HR was 71.2 ± 10.1 bpm (p < 0.001). Only 7/169 patients (4.1%) met criteria for abnormal sinus HR response: mean HR was 61.9 ± 10.6 bpm (pre-ablation), 84.6 ± 9.8 bpm (3 months), 80.1 ± 6.5 bpm (6 months) and 76.3 ± 10.1 bpm (12 months). Even at 12 months, mean HR was significantly different from that pre-ablation in this group (p = 0.033). However, in patients meeting IST-like pattern criteria, mean HR at 12 months was no longer significantly different from that pre-ablation.

Conclusion
Few patients had an abnormal sinus HR response after PVI. Peak HR was observed 3 months after PVI, but HR was still significantly increased 12 months post-ablation compared with pre-ablation. An IST-like pattern was rarely observed. In these patients, HR decreased to pre-ablation values within a year.
Conception and evaluation of a washable multimodal smart textile
Authors: Lahmann Nils A. , Müller-Werdan Ursula , Kuntz Simone , Klingehöfer-Noe Jürgen , Jaenicke Fabian , Strube-Lahmann Sandra 
Published: November 2021

AbstractSmart textiles can support people with specific needs and diseases, such as diabetes or heart disease. Currently there are efforts to combine continuous mobile monitoring with other health-related conditions. On this basis, algorithms could be developed that can be used to detect unusual or critical conditions. A study was to investigate whether a previously developed washable Multi-Modal Smart Textile (MMST), based on inexpensive materials, would provide valid and reliable results with regard to the vital parameters of pulse, temperature and mobility. The measurement of the vital parameters was carried out with the developed prototype MMST as well as with validated devices. All electronics including the rechargeable NiMH has been washed more than 30 times with different methods and it remained fully functional. The intraclass correlation coefficients (ICC) for pulse (temperature) measurement ranged between 0.036 and 0.232 (0.077 and 0.817) depending on the activity of the tested individuals (standing, sitting, lying down, moving). Cohen’s Kappa for the detection of the body position was 0.765. For the parameter of pulse, the results indicated an insufficient derivation for both validity and reliability. Due to flaws in the methodology applied, the validly and reliably for the parameter of temperature could not be determined. Valid and reliable results were obtained for the parameter mobility/change of position. If the MMST (after modification of the prototype) achieves reliable results, there are many advantages for people giving and receiving care on a budget price, even in threatening emergency situations.
Developing a new approach for the anticipation of subsurface pressure in three oil wells from various fields in Iraq
Authors: Abbas Rafid K. 
Published: November 2021

AbstractSubsurface pressure quantification is the main goal for all drilling engineers due to its vital importance to minimizing drilling costs and preventing various excavating dilemmas such as stuck pipe, pipe collapsing, lost circulation, and well kick. Formation pressure is measured directly in producing hydrocarbon zones using special equipment; however, it is difficult to obtain pore pressure measurements in other intervals; therefore, many approaches were suggested and developed to anticipate the geopressure due to its importance on the drilling operation. Traditionally, Eaton's method is the most widely used for geopressure anticipation from well logs. In the current study, a new proposed formula for geopressure determination was derived from the modified Eaton's equation which is based on the inception of the mechanical specific energy. The study was applied on three oil-producing wells from different fields in Iraq (Missan C, West Qurna 15, and Zubair 171). The estimated subsurface pressure from the new suggested approach was validated by comparison with the actual in situ subsurface pressure obtained from Drill Stem Test (DST) and Repeated Formation Test (RFT). Statistical analysis is used for the validation by applying Mean squared error (MSE) and Mean Absolute percentage Error (MAE). Encouraging results were obtained from the present research for all wells being studied. The main finding of the current work is involving a new parameter (mechanical specific energy) for subsurface pressure determination, where it was not included in the previous techniques of geopressure equations. It was found that the value of exponent (m) in the new proposed equation has a significant influence on the predicted geopressure, where (m) varies from 0.1626 to 0.6896 depending on the type of the excavated rock plus the materials that the drill bit is manufactured of, where the interaction between these components is vital. The present work could be a useful method when planning to excavate a new well adjacent to the area of the investigated wells, where special well logs are unavailable for pore pressure measurement and suitable usage of mud weight is highly needed for the overall drilling process.
Continuous Training and Deployment of Deep Learning Models
Authors: Prapas Ioannis , Derakhshan Behrouz , Mahdiraji Alireza Rezaei , Markl Volker 
Published: November 2021

AbstractDeep Learning (DL) has consistently surpassed other Machine Learning methods and achieved state-of-the-art performance in multiple cases. Several modern applications like financial and recommender systems require models that are constantly updated with fresh data. The prominent approach for keeping a DL model fresh is to trigger full retraining from scratch when enough new data are available. However, retraining large and complex DL models is time-consuming and compute-intensive. This makes full retraining costly, wasteful, and slow. In this paper, we present an approach to continuously train and deploy DL models. First, we enable continuous training through proactive training that combines samples of historical data with new streaming data. Second, we enable continuous deployment through gradient sparsification that allows us to send a small percentage of the model updates per training iteration. Our experimental results with LeNet5 on MNIST and modern DL models on CIFAR-10 show that proactive training keeps models fresh with comparable—if not superior—performance to full retraining at a fraction of the time. Combined with gradient sparsification, sparse proactive training enables very fast updates of a deployed model with arbitrarily large sparsity, reducing communication per iteration up to four orders of magnitude, with minimal—if any—losses in model quality. Sparse training, however, comes at a price; it incurs overhead on the training that depends on the size of the model and increases the training time by factors ranging from 1.25 to 3 in our experiments. Arguably, a small price to pay for successfully enabling the continuous training and deployment of large DL models.
Niclosamide-Exfoliated Anionic Clay Nanohybrid Repurposed as an Antiviral Drug for Tackling Covid-19; Oral Formulation with Tween 60/Eudragit S100
Authors: Rejinold N. Sanoj , Piao Huiyan , Choi Goeun , Jin Geun-Woo , Choy Jin-Ho 
Published: November 2021

AbstractThe ongoing pandemic, COVID-19 (SARS-CoV-2), has afflicted millions of people around the world, necessitating that the scientific community work, diligently and promptly, on suitable medicaments. Although vaccination programs have been run globally, the new variants of COVID-19 make it difficult to restrict the spread of the virus by vaccination alone. The combination of vaccination with anti-viral drug formulation is an ideal strategy for tackling the current pandemic situation. Drugs approved by the United States Food and Drug Administration (FDA), such as Remdesivir, have been found to be of little or no benefit. On the other hand, re-purposing of FDA-approved drugs, such as niclosamide (NIC), has offered promise but its applicability is limited due to its poor aqueous solubility and, therefore, low bioavailability. With advanced nano-pharmaceutical approaches, re-purposing this drug in a suitable drug-carrier for a better outcome may be possible. In the current study, an attempt was made to explore the loading of NIC into exfoliated layered double hydroxide nanoparticles (X-LDH NPs); prepared NIC-X-LDH NPs were further modified with eudragit S100 (ES100), an enteric coating polymer, to make the final product, ES100-NIC-X-LDH NPs, to improve absorption by the gastro/intestinal tract (GIT). Furthermore, Tween 60 was added as a coating on ES100-NIC-X-LDH NPs, not just to enhance its in vitro and in vivo stability, but also to enhance its mucoadhesive property, and to obtain, ultimately, better in vivo pharmacokinetic (PK) parameters upon oral administration. Release of NIC from Tween 60-ES100-NIC-X-LDH NPs was found to be greater under gastro/intestinal solution within a shorter period of time than the uncoated samples. The in vivo analysis revealed that Tween 60-ES100-NIC-X-LDH NPs were able to maintain a therapeutically relevant NIC plasma concentration in terms of PK parameters compared to the commercially available Yomesan®, proving that the new formulation might prove to be an effective oral drug-delivery system to deal with the SARS-CoV-2 viral infections. Further studies are required to ensure their safety and anti-viral efficacy.
Optimal error estimate for a space-time discretization for incompressible generalized Newtonian fluids: the Dirichlet problem
Authors: Berselli Luigi C. , Růžička Michael 
Published: November 2021

AbstractIn this paper we prove optimal error estimates for solutions with natural regularity of the equations describing the unsteady motion of incompressible shear-thinning fluids. We consider a full space-time semi-implicit scheme for the discretization. The main novelty, with respect to previous results, is that we obtain the estimates directly without introducing intermediate semi-discrete problems, which enables the treatment of homogeneous Dirichlet boundary conditions.
High-dimensional distribution generation through deep neural networks
Authors: Perekrestenko Dmytro , Eberhard Léandre , Bölcskei Helmut 
Published: November 2021

AbstractWe show that every d-dimensional probability distribution of bounded support can be generated through deep ReLU networks out of a 1-dimensional uniform input distribution. What is more, this is possible without incurring a cost—in terms of approximation error measured in Wasserstein-distance—relative to generating the d-dimensional target distribution from d independent random variables. This is enabled by a vast generalization of the space-filling approach discovered in Bailey and Telgarsky (in: Bengio (eds) Advances in neural information processing systems vol 31, pp 6489–6499. Curran Associates, Inc., Red Hook, 2018). The construction we propose elicits the importance of network depth in driving the Wasserstein distance between the target distribution and its neural network approximation to zero. Finally, we find that, for histogram target distributions, the number of bits needed to encode the corresponding generative network equals the fundamental limit for encoding probability distributions as dictated by quantization theory.
Derivation of structural weight estimation for Unmanned Combat Aerial Vehicle (UCAV)
Authors: Panahi A. , Vaziri Zanjani M. A. , Yousefi Sh. , Fazli N. , Aarabi J. 
Published: November 2021

AbstractEstimation of the structural weight of an Unmanned Combat Aerial Vehicle (UCAV) during conceptual design has proven to be a significant challenge mainly due to its unconventional configuration. We investigate development of a customised approach for structural weight estimation of UCAV based on statistical weight of the manned fighter’s components by applying minor modifications on weight formulations of fuselage, wing, empennage, power plant and landing gear. The modifications are applied by considering the corresponding differences between manned fighters and UCAVs such as manned requirements and mission variances. Some new empirical formulas for estimating the weight of UCAV’s components are proposed. Results for the empty weight estimation are validated against actual values of some well-known UCAVs. Moreover, the structural weight is validated against the benchmark UCAV case studies. The results show that the ratio of structural to takeoff weight for UCAVs is approximately between 20% to 10%. Finally, a generalised equation is developed for estimating the structural weight of UCAVs in conceptual design phase.
The Mariel Cubans and John Lewis's Legacy on Human Rights
Authors: Camp Michael 
Published: November 2021

AbstractThis essay examines Representative John Lewis's engagement with the 1987 uprising of Cuban immigrant detainees held in Atlanta's federal penitentiary, which occurred near the beginning of Lewis's time in Congress. Cuban prisoners at the penitentiary took control of the institution and detained several hostages in order to forestall their deportation back to Cuba. After the uprising ended, in contrast to other public figures who advocated harsh punitive treatment, Lewis urged mercy and compassion for the prisoners. Lewis's involvement in the story revealed his underlying understanding of human rights, which he connected to his experiences in the civil rights movement of the 1960s. This broad conception of human rights shaped his engagement with issues of immigration throughout the remainder of his congressional career, especially during the administration of President Donald Trump. Lewis's engagement with issues of immigration is also especially noteworthy in light of metro Atlanta's emergence as a key site for the settlement of immigrants and refugees from around the world, which continues to shape the politics of the metro area.
Race and non-electoral political participation in Brazil, South Africa, and the United States
Authors: Fialho Fabrício M. 
Published: November 2021

AbstractThis paper examines the context-dependent role of race as a predictor of non-electoral political participation. Prior country-level studies have documented group-level differences in a variety of forms of participation in South Africa and the United States, but have found few to no differences in Brazil. Why are members of one group more engaged in certain political activities than members of other groups only in specific contexts? Why do members of socioeconomically deprived groups, such as non-Whites, participate more than better-off groups in acts that require group mobilization in South Africa and the United States but not in Brazil? Results from the World Values Survey and the International Social Survey Programme show that Blacks and Coloureds in South Africa and Blacks in the United States participate more than Whites in activities that demand prior organization and mobilization, whereas group differences are negligible in Brazil. I argue that (1) race as a driver of political mobilization is conditional on the existence of politicized racial identities; (2) members of groups that share a strong collective identity participate in direct political action more than predicted by their socioeconomic background; (3) politicization of identities is the product of racial projects that deploy the state apparatus to enforce group boundaries for the implementation of segregationist policies as well as the reactions against them; and (4) by enforcing group boundaries, those systems unintentionally create the conditions for the formation of politicized group identities. In the absence of such requisites, political mobilization along racial lines would be weak or nonexistent.