bluuebunny/crossref_metadata_2025 huggingface dataset:
Patient and aneurysm factors associated with aneurysm recanalization after coiling
Authors: Pierot Laurent , Barbe Coralie , Thierry Aurore , Bala Fouzi , Eugene Francois , Cognard Christophe , Herbreteau Denis , Velasco Stéphane , Chabert Emmanuel , Desal Hubert , Aggour Mohamed , Rodriguez-Regent Christine , Gallas Sophie , Sedat Jacques , Marnat Gaultier , Sourour Nader , Consoli Arturo , Papagiannaki Chrysanthi , Spelle Laurent , White Phil
Published: November 2021

Background

One limitation of the endovascular treatment of intracranial aneurysms is aneurysm recanalization. The Analysis of Recanalization after Endovascular Treatment of intracranial Aneurysm (ARETA) study is a prospective multicenter cohort study evaluating the factors associated with recanalization after endovascular treatment.

Methods

The current analysis is focused on patients treated by coiling or balloon-assisted coiling (BAC). Postoperative, mid-term vascular imaging, and evolution of aneurysm occlusion were independently evaluated by two neuroradiologists. A 3-grade scale was used for aneurysm occlusion (complete occlusion, neck remnant, and aneurysm remnant) and for occlusion evolution (improved, stable, and worsened). Recanalization was defined as any worsening of aneurysm occlusion.

Results

Between December 2013 and May 2015, 16 French neurointerventional departments enrolled 1289 patients. A total of 945 aneurysms in 908 patients were treated with coiling or BAC. The overall rate of aneurysm recanalization at mid-term follow-up was 29.5% (95% CI 26.6% to 32.4%): 28.9% and 30.3% in the coiling and BAC groups, respectively. In multivariate analyses factors independently associated with recanalization were current smoking (36.6% in current smokers vs 24.5% in current non-smokers (OR 1.8 (95% CI 1.3 to 2.4); p=0.0001), ruptured status (31.9% in ruptured aneurysms vs 25.1% in unruptured (OR 1.5 (95% CI 1.1 to 2.1); p=0.006), aneurysm size ≥10 mm (48.8% vs 26.5% in aneurysms <10 mm (OR 2.6 (95% CI 1.8 to 3.9); p<0.0001), wide neck (32.1% vs 25.8% in narrow neck (OR 1.5 (95% CI 1.1 to 2.1); p=0.02), and MCA location (34.3% vs 28.3% in other locations (OR 1.5 (95% CI 1.0 to 2.1); p=0.04).

Conclusions

Several factors are identified by the ARETA study as playing a role in aneurysm recanalization after coiling: current smoking, aneurysm status (ruptured), aneurysm size (≥10 mm), neck size (wide neck), and aneurysm location (middle cerebral artery). This finding has important consequences in clinical practice.

Trial registration number

URL:http://www.clinicaltrials.gov; Unique Identifier:NCT01942512.
Seroprevalence of the SARS-CoV-2 antibody in healthcare workers: a multicentre cross-sectional study in 10 Colombian cities
Authors: Malagón-Rojas Jeadran Nevardo , Mercado-Reyes Marcela , Toloza-Pérez Yezith G , Parra Barrera Eliana L , Palma Marien , Muñoz Esperanza , López Ronald , Almentero Julia , Rubio Vivian V , Ibáñez Edgar , Téllez Eliana , Delgado-Murcia Lucy G , Jimenez Claudia P , Viasus-Pérez Diego , Galindo Marisol , Lagos Luisa
Published: November 2021

Background

Healthcare workers are at increased risk of infection due to occupational exposure to SARS-CoV-2-infected patients. The objective of this study was to determine the seroprevalence of SARS-CoV-2 in healthcare workers in Colombia.

Methods

This study is a cross-sectional study focused on estimating the seroprevalence of SARS-CoV-2 antibodies in healthcare workers from 65 hospitals in 10 cities in Colombia during the second semester of 2020. The seroprevalence was determined using an automated immunoassay (Abbott SARS-CoV-2 CLIA IgG). The study included a survey to establish the sociodemographic variables and the risk of infection. A multivariate model was used to evaluate the association between the results of seroprevalence and risk factors.

Results

The global seroprevalence of antibodies against SARS-CoV-2 was 35% (95% Bayesian CI 33% to 37%). All the personnel reported the use of protective equipment. General services personnel and nurses presented the highest ratios of seroprevalence among the healthcare workers. Low socioeconomic strata have shown a strong association with seropositivity.

Conclusion

This study estimates the prevalence of SARS-CoV-2 infection among healthcare workers. Even though all the personnel reported the use of protective equipment, the seroprevalence in the general services personnel and nurses was high. Also, a significant difference by cities was observed.
Measurement of inbreeding depression in Rhododendron kaempferi: seed production, germination, juvenile survival, and growth
Authors: Takahashi Keigo , Itino Takao
Published: November 2021

To understand the reproductive ecology of a plant species with both selfing and outcrossing reproductive systems, it is important to know how selfed individuals contribute to the maintenance of a population. Further, examination of the magnitude of inbreeding depression after pollination is essential for the accurate measurement of reproductive success. In this study, we investigated the characteristics of viable seeds and seedlings of Rhododendron kaempferi Planch. in a region where the bumblebee pollinator Bombus ardens Smith, 1879 are abundant. In a hand-pollination experiment, the fruit set from self-pollination was 32%, significantly lower than that from outcross-pollination (81%). The number of seeds per fruit from self-pollination was one sixth the number from outcross-pollination. However, the number of seeds per fruit was negatively correlated with the mass per seed. In addition, the germination rate was low when the seed mass was light. Although selfed seeds could germinate, 89% of the seedlings died within a year. The inbreeding depression coefficient one year after sowing was very high (0.89). These results indicate that R. kaempferi shows extremely strong selection for outcrossing but maintains a slight selfing potential in a natural population in central Japan.
Food web incorporation of marine-derived nutrients after the reintroduction of endangered inner Bay of Fundy Atlantic salmon (Salmo salar)
Authors: Bryson Grace E. , Kidd Karen A. , Samways Kurt M.
Published: November 2021

Inner Bay of Fundy Atlantic salmon (Salmo salar) are endangered anadromous fish that have the potential to provide marine-derived nutrients (MDNs) to freshwater ecosystems depending on their population abundance. Salmon have been reintroduced to the Upper Salmon River, but not to the adjacent Point Wolfe River, in Fundy National Park, New Brunswick, Canada. This study determined whether stocking of adult salmon increased the productivity of the river. To examine the incorporation of MDNs, biofilm, leaf litter, Perlidae, Heptageniidae and brook trout (Salvelinus fontinalis) were sampled pre- and post-spawning in 2015–2017 from down- and upstream of a natural barrier in both rivers and analyzed for carbon (δ13C) and nitrogen (δ15N) isotopes. After salmon spawning in each year, all organisms at the downstream site of the stocked river increased in δ13C and δ15N, with the greatest enrichment in brook trout (δ13C: −23.97‰ to −21.10‰, δ15N: +6.36‰ to +10.73‰). The proportion of MDNs in brook trout after salmon spawning (2015: 23.4%, 2016: 40.7%, 2017: 37.4%) also increased with higher numbers of released adult salmon. Results support the importance of salmon restoration for increasing the proportion of MDNs and productivity in rivers in Atlantic Canada.
The role of hatcheries in the decline of Lake Ontario Atlantic salmon
Authors: Morrison Brian P. , Peiman Kathryn S.
Published: November 2021

Lake Ontario Atlantic salmon (Salmo salar) were one of the first species of fish to be cultured in Canada. Their story goes from abundance in the 1700s to protective legislation in 1807, then hatchery culture in 1866 and finally ends in extirpation in 1898. The standard narrative is that Samuel Wilmot’s hatchery efforts briefly staved off their loss from the Lake Ontario basin. However, that story is replete with inaccurate assumptions, unfounded faith in technological solutions, and a belief that numbers of fish released was an accurate measure of success. We challenge the narrative around the perceived benefits of these hatchery efforts and suggest instead that they contributed to the decline of Atlantic salmon in Lake Ontario through the mining of wild gametes, transferring eggs out of basin, mixing locally adapted populations across streams, and the negative genetic effects of releasing hatchery fish.
Calculation of the contribution to muon g − 2 due to the effective anomalous three boson interaction and the new experimental result
Authors: Arbuzov B. A. , Zaitsev I. V.
Published: November 2021

Using the approach based on Bogoliubov compensation principle is applied to the calculation of a contribution to the muon [Formula: see text]. Using the previous results on spontaneous generation of the effective anomalous three-boson interaction we calculate the contribution, which proves to agree with the well-known discrepancy. The calculated quantity contains no adjusting parameters but the experimental values for the muon and the [Formula: see text]-boson masses. The result can be considered as a confirmation of the approach.
Classification of Diabetic Retinopathy using Capsules
Authors: Vanusha D. , Amutha B.
Published: November 2021

Deep learning models have performed exceptionally well in detection of diabetic retinopathy. Most of these existing works either use Multi Layered Perceptron (MLP) or Convolutional Neural Network (CNN) based models. A significant drawback of these models is their inability to retain spatial dependencies as we go deeper into the network. Because of such issue, these models focus only on extraction of feature maps which help in classification or detection. In recent years’ transformers have shown enormous promise in both natural language processing and computer vision, due to which there have been significant work on transformer based techniques for image classification and object detection. One important model used in this research work is the Capsule Network which uses Set Transformers to perform vision tasks with high accuracy and has the capability to maintain spatial dependencies throughout the process. In this work, we leverage the power of capsules to the diabetic retinopathy classification and detection problem and trained capsules for classification of retinal fundus images are considered which were categorize into five different classes depending on the severity of retinopathy. Further, we also propose a sliding window based detector which can pinpoint the exact position of a blood burst in the retina which will ease the job for ophthalmologists while studying retinal fundus. From our experiments we found that capsules provide better results than existing convolutional neural network and multi layered perceptron based approaches in standard retinopathy datasets.
Examine Fuzzy System to Present an Equilibrium Model for the Internal Pressure Losses of Alpha Type Stirling Engine: Comparison with ANN Model
Authors: Musmar Sa’ed A. , Tlili Iskander , Al-Halhouli Ala’Aldeen , Mucciardi Frank
Published: November 2021

Global warming associated with the greenhouse effect urge finding alternative energy strategies concerned with sustainable energy resources that are environmentally friendly and provide energy saving. Waste heat recovery engines are attracting devices that convert usually wasted energy to valuable mechanical or electrical energy. The current research aims to develop a mathematical model to investigate the effects of regenerator physical dimensions on the alpha Stirling engine performance indicators. A mathematical model integrating an internal pressure drop has been proposed to act as a thermodynamic optimization tool for the Stirling engine. The main conclusion was that both geometrical factors and working fluid initial charge (gas mass) craft the performance parameters of alpha type Stirling engine that operates with air as working material. After that, Artificial neural networks of Levenberg Marquardt and Orthogonal Distance Regression models, and Fuzzy systems trained for Mass Charge from M = 0.002 to 0.004 Kg are compared to find the least uncertainty. Results revealed that the Fuzzy system and Orthogonal Distance Regression model could predict more effectively than the Levenberg Marquardt model.
Time Series Forecasting Model Based on Intuitionistic Fuzzy Set via Equal Distribution of Hesitancy De-I-Fuzzification
Authors: Nik Badrul Alam Nik Muhammad Farhan Hakim , Ramli Nazirah
Published: November 2021

The fuzzy time series forecasting model is a powerful tool in forecasting the time series data. The nature of the fuzzy set exhibits its role in handling the uncertainty of the data. The intuitionistic fuzzy set (IFS) is a generalization of a fuzzy set that makes the forecasting process more precise and accurate. This paper proposes a new fuzzy forecasting model based on IFS via the de-i-fuzzification approach, namely equal distribution of hesitancy. The proposed model consists of four main parts; the fuzzification of historical data; the establishment of the IFS; the de-i-fuzzification; and the defuzzification. For the fuzzification, the historical data is partitioned into 14 intervals using the frequency density-based method and trapezoidal fuzzy numbers are used to fuzzify the data. The data are then converted into IFS. The data in IFS form is reduced to fuzzy set using equally distributed with the degree of hesitancy approach. The arithmetic rules based on centroid defuzzification is used to calculate the forecasted output. The proposed model shows a better performance than the existing forecasting models based on IFS, indicating that the equal distribution of hesitancy de-i-fuzzification managed to handle the non-determinism in the forecasting with simplified procedure. In the future, an improved method will be proposed to defuzzify the IFS into crisp values without going through the de-i-fuzzification process, yet preserving the nature of IFS.
Enhanced Inventory Management Using Blockchain Technology Under Cloud Sector Enabled by Hybrid Multi-Verse with Whale Optimization Algorithm
Authors: Govindasamy Chinnaraj , Antonidoss Arokiasamy
Published: November 2021

Inventory cost control is an essential factor in supply chain management. If the supplier’s inventory is insufficient, then the chance to trade the product will be reduced. The manufacturer’s inadequate material inventory will have an effect in termination of production, delays, and a waste of resources and time. On the other hand, postponed transportation will certainly raise costs such as transportation costs and cancellation of orders. Therefore, the operation costs of enterprises will be more, which will lower profits. In conventional supply chains, inventory costs control is not feasible for the view of the entire supply chain. The main intent of this paper is to plan for intelligent inventory management using blockchain technology under the cloud sector. The inventory management of the supply chain includes “multiple suppliers, a manufacturer, and multiple distributors”. The proposed inventory management models consider some significant costs like “transaction cost, inventory holding cost, shortage cost, transportation cost, time cost, setup cost, backordering cost, and quality improvement cost”. This multi-objective cost function is minimized by a novel hybrid optimization algorithm; the concept of WOA is integrated to produce the new algorithm which is termed as Whale-based Multi Verse Optimization (W-MVO) algorithm. For securing the data of distributors, using blockchain technology in a cloud environment helps from the leakage of data to other unauthorized users. Once the cost is reduced in all aspects based on the proposed hybrid optimization algorithm, the distributer will store the concerning data in the blockchain under the cloud sector, where each distributer holds a hash function to store its data, which cannot be restored by the other distributers. The valuable performance analysis over the conventional optimization algorithms proves the effective and reliable performance of the proposed model over the conventional models.
ACTIVITIES WITHIN CIRCULAR-ORIENTED INNOVATION PROCESS: CASES OF BIOMATERIAL DEVELOPMENT
Authors: OFTERDINGER JANIKA , DLUGOBORSKYTE VYTAUTE , HERSTATT CORNELIUS
Published: November 2021

Within the research field of innovation management, the so-called circular-oriented innovations are focused on combining circular economy tenets within the development of innovation. Even though academia agrees that an economic transition has to develop from the bottom up, studying the implementation of circular economy on micro-level has been thus far neglected. Thus, the paper examines the circular-oriented innovation specific activities within the general innovation process and its distinct phases. Via multiple case study, the paper analyses the development of innovations suitable for the biological cycle of circular economy in the industry of biodegradable plastic substitutes. The findings show that circular economy aspects influence the innovation development from its very beginning. Starting from the triggering of idea generation, the end-of-life considerations and material choice show high importance in the front-end of innovation. Moreover, the research shows the high importance of cross-cycle and cross-sector collaborations throughout the entire development process.
Electrical creep and fatigue in 0.5Ba(Zr0.2Ti0.8)O3-0.5(Ba0.7Ca0.3)TiO3 ceramics
Authors: Sharma Moolchand , Patel Satyanarayan , Arockiarajan A. , Vaish Rahul
Published: November 2021

In this study, the creep and fatigue characterization is performed for 0.5Ba(Zr[Formula: see text]Ti[Formula: see text]O[Formula: see text]0.5(Ba[Formula: see text]Ca[Formula: see text]TiO3 (BZT-BCT) bulk ferroelectric ceramics. A function generator is used to generate the required waveform of the voltage amplifier for fatigue and creep analysis. The evolution of polarization is studied for electrical creep. The effects of temperature and electric field on the electric displacement are studied. Hysteresis–butterfly loops are analyzed for fatigue tests for different thermal loads up to 106 cycles. It inheres that the material is stable below 75[Formula: see text]C and can withstand high cycle fatigue loads (25 Hz, ± 1.5 kV/mm).
3D seismic interpretation and fault slip potential analysis from hydraulic fracturing in the Bowland Shale, UK
Authors: Nantanoi Sirawitch , Rodríguez-Pradilla Germán , Verdon James
Published: November 2021

The Bowland Shale Formation is one of the most promising targets for unconventional exploration in the United Kingdom, with estimated resources large enough to supply the country's entire natural gas consumption for 50 years. However, development of the Bowland Shale has stalled due to concerns over hydraulic-fracturing-induced seismicity. Only three wells have been drilled and hydraulic-fractured to date in the Bowland Shale, and all three have produced levels of seismicity of sufficient magnitude to be felt at the surface. Susceptibility to induced seismicity will be determined by the presence of critically stressed faults. However, such faults can go undetected in conventional interpretation of 2D or 3D seismic surveys if they are shorter than the resolution retrievable from a seismic survey, or if they have low (and in some cases even zero) vertical displacement. In such cases, the faults that cause induced seismicity may only be visible via microseismic observations once they are reactivated. To better identify fault planes from 3D seismic images, and their reactivation potential due to hydraulic fracturing, a high-resolution fault-detection attribute was tested in a 3D seismic survey that was acquired over the Preston New Road site, where two shale-gas wells were hydraulic-fractured in the Bowland Shale in 2018 and 2019, obtaining fault planes with lengths between 400 and 1500 m. Fault slip potential was then estimated by integrating the obtained faults with the formation's stress and pore pressure conditions (with the Bowland shale also being significantly overpressured), and several critically stressed faults were identified near the previously hydraulic fractured wells. However, the faults that induced the largest seismic events in the Preston New Road site, of
c.
200 m in length for seismic events of magnitudes below 3.0 (as imaged with a multicomponent, downhole microseismic monitoring array deployed during the hydraulic-fracturing stimulations), could not be identified in the 3D seismic survey, which only mapped fault planes larger than 400 m in length.
PACMHCI V5, ISS, November 2021 Editorial
Authors: Fjeld Morten , Jetter Hans-Christian , Isenberg Petra , Hancock Mark
Published: November 2021

It is our great pleasure to welcome you to this issue of the Proceedings of the ACM on Human-Computer Interaction, the second to focus on the contributions from the research community Interactive Surfaces and Spaces (ISS). Interactive Surfaces and Spaces increasingly pervade our everyday life, appearing in various sizes, shapes, and application contexts, offering a rich variety of ways to interact. This diverse research community explores the design, development, and use of new and emerging interactive surface technologies and interactive spaces.

The call for articles for this issue on ISS attracted 77 submissions, from all over the world. This issue has 23 papers, 4 submitted in February 2021 and 19 submitted in July 2021. After the winter round, 4 (total of 19 articles, 21.1%) articles were accepted and 5 (26.3%) articles required major revisions. After the summer round, 19 (total of 58 articles, 32.8%) articles were accepted, and 18 (31,0%) articles required major revisions. The editorial committee worked hard over the two iterations of the review process, winter and summer rounds, to arrive at final decisions. In total, counting both the winter and the summer rounds, 23 articles (total of 77 articles, 29.9%) were accepted. All authors of the accepted articles are invited to present at the ISS conference from November 14--17, 2021.

This issue exists because of the dedicated volunteer effort of 31 senior editors who served as Associate Chairs (ACs), 105 expert reviewers in the winter round, and 206 expert reviewers in the summer round to ensure high quality and insightful reviews for all articles. Reviewers and committee members were kept constant for papers that submitted to both rounds. The Editorial Board is presented here: https://iss.acm.org/2021/organization/editorial_board
ADQDA
Authors: Liu Jiali , Eagan James
Published: November 2021

Affinity diagramming is widely applied to analyze qualitative data such as interview transcripts. It involves multiple analytic processes and is often performed collaboratively. Drawing on interviews with three practitioners and upon our own experience, we show how practitioners combine multiple analytic processes and adopt different artifacts to help them analyze their data. Current tools, however, fail to adequately support mixing analytic processes, devices, and collaboration styles. We present a vision and prototype ADQDA, a cross-device, collaborative affinity diagramming tool for qualitative data analysis, implemented using distributed web technologies. We show how this approach enables analysts to appropriate available pertinent digital devices as they fluidly migrate between analytic phases or adopt different methods and representations, all while preserving consistent analysis artifacts. We validate this approach through a set of application scenarios that explore how it enables new ways of analyzing qualitative data that better align with identified analytic practices.
Analyzing Midair Object Pointing Mappings for Smart Display Input
Authors: Zhang Futian , Mizobuchi Sachi , Zhou Wei , Lank Edward
Published: November 2021

One common task when controlling smart displays is the manipulation of menu items. Given current examples of smart displays that support distant bare hand control, in this paper we explore menu item selection tasks with three different mappings of barehand movement to target selection. Through a series of experiments, we demonstrate that Positional mapping is faster than other mappings when the target is visible but requires many clutches in large targeting spaces. Rate-based mapping is, in contrast, preferred by participants due to its perceived lower effort, despite being slightly harder to learn initially. Tradeoffs in the design of target selection in smart tv displays are discussed.
Multi-Touch Querying on Data Physicalizations in Immersive AR
Authors: Herman Bridger , Omdal Maxwell , Zeller Stephanie , Richter Clara A. , Samsel Francesca , Abram Greg , Keefe Daniel F.
Published: November 2021

Data physicalizations (3D printed terrain models, anatomical scans, or even abstract data) can naturally engage both the visual and haptic senses in ways that are difficult or impossible to do with traditional planar touch screens and even immersive digital displays. Yet, the rigid 3D physicalizations produced with today's most common 3D printers are fundamentally limited for data exploration and querying tasks that require dynamic input (e.g., touch sensing) and output (e.g., animation), functions that are easily handled with digital displays. We introduce a novel style of hybrid virtual + physical visualization designed specifically to support interactive data exploration tasks. Working toward a "best of both worlds" solution, our approach fuses immersive AR, physical 3D data printouts, and touch sensing through the physicalization. We demonstrate that this solution can support three of the most common spatial data querying interactions used in scientific visualization (streamline seeding, dynamic cutting places, and world-in-miniature visualization). Finally, we present quantitative performance data and describe a first application to exploratory visualization of an actively studied supercomputer climate simulation data with feedback from domain scientists.
Ultrasound-driven Curveball in Table Tennis
Authors: Morisaki Tao , Mori Ryoma , Mori Ryosuke , Serizawa Kohki , Makino Yasutoshi , Itoh Yuta , Yamakawa Yuji , Shinoda Hiroyuki
Published: November 2021

Augmented Human (AH) is a research field enhancing human physical abilities or supporting human activity using advanced technologies. As one of the AH approaches, previous studies have attached an actuator to a human body or tools used for an activity. The attached actuators are used to control their movements to support an activity. In this study, instead of attaching actuators, we propose to directly apply noncontact ultrasound force to a lightweight tool to manipulate it. The advantage of using noncontact force is that users do not need to wear a specific device and to process tools used for the activity. As a proof-of-concept system, we developed an ultrasound-based curveball system by which table tennis players can shoot a curveball regardless of their physical ability. In the system, a moving ping-pong ball (PPB) is a target tool for remote manipulation. The system curves the trajectory of a moving PPB by continuously focusing ultrasound on it. Users can control the curve timing and the curve direction (left or right) using a racket-shaped controller. In the user study, we conducted an actual table tennis match using the curveball system and qualitatively confirmed that the player using the system had the upper hand. Another user study using a ball dispenser quantitatively showed that the ultrasound-driven curveball increased the number of mistakes of the opponent player 2.95 times. These results indicate that the proposed concept is feasible.
Open Problems Column
Authors: Gasarch William
Published: November 2021

This issue's Open Problem Column is by Lance Fortnow and its titled Worlds to Die For: Open Oracle Questions for the 21st Century.
SIGACT News Complexity Theory Column 110
Authors: Hemaspaandra Lane A.
Published: November 2021

My deepest thanks to Beatrice and Carlo for their fascinating article, Quantum Finite Automata: From Theory to Practice. Regarding the extent to which their article brings to life both parts of its subtitle... wow! And I think Section 4 is an absolute first for this column; please don't miss it!
Guest Column
Authors: Mereghetti Carlo , Palano Beatrice
Published: November 2021

Quantum computing is a prolific research area, halfway between physics and computer science [27, 29, 52]. Most likely, its origins may be dated back to 70's, when some works on quantum information began to appear (see, e.g., [34, 37]). In early 80's, R.P. Feynman suggested that the computational power of quantum mechanical processes might be beyond that of traditional computation models [25]. Almost at the same time, P. Benioff already proved that such processes are at least as powerful as Turing machines [9]. In 1985, D. Deutsch [22] proposed the notion of a quantum Turing machine as a physically realizable model for a quantum computer. From the point of view of structural complexity, E. Bernstein and U. Vazirani introduced in [20] the class BQP of problems solvable in polynomial time on quantum Turing machines, focusing attention on relations with the corresponding deterministic and probabilistic classes P and BPP, respectively. Several works in the literature explored classical issues in complexity theory from the quantum paradigm perspective (see, e.g., [7, 60, 61]).
Distributed Computing Column 83 Five Ways Not To Fool Yourself
Authors: Alistarh Dan
Published: November 2021

Overview. In this edition of the column, we have a very interesting and instructive contribution from Tim Harris (Microsoft, Cambridge, UK), whose goal is to provide a systematic overview of practical, "hands-on" techniques for the correct performance evaluation of a complex distributed system.
Database Theory Column Report on PODS 2021
Authors: Pichler Reinhard
Published: November 2021

The 40th edition of the ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS) was held from June 20 to June 25, 2021, in Xi'an, Shaanxi, China. Due to the COVID-19 pandemic, it was organized in hybrid mode, with a local event primarily targeting the Chinese data management community and as a virtual (on- line) conference for the international community. As in previous years, the symposium was held jointly with the ACM International Conference on Management of Data (SIGMOD). PODS focuses on theoretical aspects of data management systems, and the co-location with SIGMOD stimulates interaction between theory-oriented and system-oriented research.
Stigmatized Work and Stigmatized Workers
Authors: Kreiner Glen , Mihelcic Christine A. , Mikolon Sven
Published: November 2021

Stigmas pervade organizational life. A stigma is a discrediting social evaluation that devalues an individual or group. We review research on stigmatized work and stigmatized workers, with a particular emphasis on how people become stigmatized and what they (and others) do about it. To do so, we connect stigma to other concepts in its nomological net and compare multiple models of stigma dynamics. We consider the intertwining nature of stigma and identity/image, how context affects stigma, and how stigma is managed by both the stigmatized and the nonstigmatized. We also offer critiques of key blind spots in workplace stigma research and point toward future research in this area that is more interconnected with other literatures and more inclusive of overlooked populations. Our vantage point is that workplace stigma continues to be an exciting domain of research with a high potential for theoretical discoveries and practical applications.
Mg–Sn Alloys as Anodes for Magnesium-Air Batteries
Authors: Tong Fanglei , Chen Xize , Teoh Teik Ee , Wei Shanghai , Waterhouse Geoffrey I. N. , Gao Wei
Published: November 2021

Three Mg–Sn alloys (with Sn contents of 1, 3, and 5 wt%) were investigated as anodes for magnesium-air batteries. The effect of Sn addition on the microstructure, electrochemical behaviour and battery discharge properties of Mg alloys was studied. Addition of Sn improves the operational voltage of Mg at low to high current densities. At low current densities ≤2 mA·cm−2, Mg-5Sn exhibits better battery discharge performance than pure Mg and other Mg–Sn alloy anodes. At current densities higher than 5 mA·cm−2, Mg-1Sn delivered the best battery discharge performance, evidenced by an anodic efficiency of 51.7%, specific capacity of 1133 mAh g−1 and specific energy density of 1208 mWh g−1 at 10 mA·cm−2. The underlying mechanism by which Mg–Sn alloys improve Mg-air battery performance is discussed.
A Platinum Micro-Reference Electrode for Impedance Measurements in a PEM Water Electrolysis Cell
Authors: Hartig-Weiß Alexandra , Bernt Maximilian , Siebel Armin , Gasteiger Hubert A.
Published: November 2021

We present a platinum wire micro-reference electrode (Pt-WRE) suitable for recording individual electrochemical impedance spectra of both the anode and the cathode in a proton exchange membrane water electrolyzer (PEM-WE). For this purpose, a thin, insulated Pt-wire reference electrode (Pt-WRE) was laminated centrally between two 50μm Nafion® membranes, whereby the potential of the Pt-WRE is determined by the ratio of the local H2and O2permeation fluxes at the tip of the Pt-WRE. Impedance analysis with the Pt-WRE allows determination of the proton sheet resistance of the anode, the anode catalyst layer capacitance, and the high-frequency resistance (HFR) of both electrodes individually, using a simple transmission-line model. This new diagnostic tool was used to analyze performance degradation during an accelerated stress test (AST), where low and high current densities were alternated with idle periods without current (i.e., at open circuit voltage (OCV)), mimicking the fluctuating operation of a PEM-WE with renewable energy. Our analysis revealed that the increasing HFR that was observed over the course of the OCV-AST, which is the main cause for the observed performance decrease, can unequivocally be assigned to an increasing contact resistance between the anode electrode and the porous transport layer.
Research on the Characteristics of Food Impaction with Tight Proximal Contacts Based on Deep Learning
Authors: Cheng Yitong , Wang Zhijiang , Shi Yue , Guo Qiaoling , Li Qian , Chai Rui , Wu Feng
Published: November 2021

Objective. Based on deep learning, the characteristics of food impaction with tight proximal contacts were studied to guide the subsequent clinical treatment of occlusal adjustment. At the same time, digital model building, software measurement, and statistical correlation analysis were used to explore the cause of tooth impaction and to provide evidence for clinical treatment. Methods. Volunteers with (

n
=
250

) and without (

n
=
250

) tooth impaction were recruited, respectively, to conduct a questionnaire survey. Meanwhile, models were made and perfused by skilled clinical physicians for these patients, and characteristics such as adjacent line length, adjacent surface area, tongue abduction gap angle, buccal abduction gap angle, and occlusal abduction gap angle were measured. A normality test, differential analysis, correlation analysis of pathological characteristics of the impaction group, principal component analysis (PCA), and binary logistic regression analysis were performed. Results. The adjacent line length, adjacent surface area, tongue abduction gap angle, buccal abduction gap angle, and occlusal abduction gap angle all met normal distribution. There were statistically significant differences in adjacent line length (

p
<
0.001

), adjacent surface area (

p
<
0.001

), and occlusal abduction gap angle (

p
<
0.001

) between the two groups. After dimensionality reduction by PCA on characteristics, adjacent line length, adjacent surface area, buccal abduction gap angle, and occlusal abduction gap angle had a strong correlation with the principal components. Binary logistic regression analysis showed that adjacent line length and adjacent surface area had positive effects on impaction. The buccal abduction gap angle and occlusal abduction gap angle had a significant negative influence on impaction. Conclusion. Adjacent line length, adjacent surface area, buccal abduction gap angle, and occlusal abduction gap angle are independent factors influencing food impaction.
SARS-CoV-2 Infection in Kidney Transplant Recipients: A Single-Centre Study of 20 Cases from India
Authors: Tatapudi Ravi Raju , Kopparti Venkateswara Rao , Poosapati Anusha , Metta Srinivas , Gongada Atchyutha Rao , Vedulla Balakrishna
Published: November 2021

Introduction. The second wave of COVID-19 has spread across India causing unprecedented misery to people since March 2021. Kidney transplant recipients (KTRs) are at an increased risk of severe infection. Their outcomes appear to be worse than those in the general population. There is no robust evidence or consensus to support any form of treatment protocol or modification of immunosuppression in KTRs with COVID-19. There is a need to develop effective and safe therapeutic protocols for this frail population. Remdesivir is the only approved antiviral drug in COVID-19 till now. Methods. We describe clinical features, role of HRCT, therapeutic protocols, and mortality rate of 20 KTRs with SARS-CoV-2 infection. Results. Complete recovery was seen in 8 (40%) patients monitored at home. 12 (60%) patients with HRCT scores more than 8/25 were hospitalized. 11 (55%) had hypoxia, of these 8 (40%) had mild hypoxia, 1 (5%) required NIV, and 2 (10%) needed mechanical ventilation. Immunosuppression was modified in all the patients. Remdesivir and dexamethasone were administered to the hospitalized patients. 1 (5%) patient had AKI requiring RRT. 1 (5%) patient expired, and 1 still hospitalized. 10 of the hospitalized patients recovered. Out of the total 20 patients, 18 (90%) recovered completely within two weeks of infection. Conclusion. Clinical presentation of COVID-19 in KTRs was similar to nontransplant patients. Early hospitalisation and assessing the severity by HRCT were important. Continuing tacrolimus and administering remdesivir and dexamethasone reduced the incidence of renal failure and improved survival rates.
A Novel Context Aware Joint Segmentation and Classification Framework for Glaucoma Detection
Authors: Ganesh S. Sankar , Kannayeram G. , Karthick Alagar , Muhibbullah M.
Published: November 2021

Glaucoma is a chronic ocular disease characterized by damage to the optic nerve resulting in progressive and irreversible visual loss. Early detection and timely clinical interventions are critical in improving glaucoma-related outcomes. As a typical and complicated ocular disease, glaucoma detection presents a unique challenge due to its insidious onset and high intra- and interpatient variabilities. Recent studies have demonstrated that robust glaucoma detection systems can be realized with deep learning approaches. The optic disc (OD) is the most commonly studied retinal structure for screening and diagnosing glaucoma. This paper proposes a novel context aware deep learning framework called GD-YNet, for OD segmentation and glaucoma detection. It leverages the potential of aggregated transformations and the simplicity of the YNet architecture in context aware OD segmentation and binary classification for glaucoma detection. Trained with the RIGA and RIMOne-V2 datasets, this model achieves glaucoma detection accuracies of 99.72%, 98.02%, 99.50%, and 99.41% with the ACRIMA, Drishti-gs, REFUGE, and RIMOne-V1 datasets. Further, the proposed model can be extended to a multiclass segmentation and classification model for glaucoma staging and severity assessment.
Evaluation of Patients with Parkinson’s Disease in Intensive Care Units: A Cohort Study
Authors: Réa-Neto Álvaro , Dal Vesco Bruna C. , Bernardelli Rafaella S. , Kametani Aline M. , Oliveira Mirella C. , Teive Hélio A. G.
Published: November 2021

Background. Parkinson’s disease affects approximately 1% of the worldwide population older than 60 years. This number is estimated to double by 2030, increasing the global burden of the disease. Patients with Parkinson’s disease are hospitalized 1.5 times more frequently and for longer periods than those without the disease, increasing health-related costs. Objective. To compare the characteristics and outcome of patients with and without Parkinson’s disease admitted to intensive care units (ICUs). Methods. Historical cohort study of ICU admissions in a Brazilian city over 18 years. All patients with Parkinson’s disease identified were matched for age, sex, year, and place of hospitalization with patients without the disease randomly selected from the same database. Results. The study included 231 patients with Parkinson’s disease (PD group) and 462 controls without the disease (NPD group). Compared with patients in the NPD group, those in the PD group were more frequently admitted with lower level of consciousness and increased APACHE II severity score but required less frequently vasoactive drugs. In total, 42.4% of the patients in the PD group were admitted to the ICUs due to sepsis or trauma. Although these patients had longer hospital stay, the mortality rates were comparable between groups. Parkinson’s disease was not associated with mortality, even when controlled for associated factors of disease severity. Conclusion. Although patients with Parkinson’s disease were admitted with higher severity scores and remained in the ICU for a longer time, their mortality rate was not higher than that in patients without the disease.
Experimental Study of the Adsorption of Nitrogen and Phosphorus by Natural Clay Minerals
Authors: Fan Tingyu , Wang Miao , Wang Xingming , Chen Yingxiang , Wang Shun , Zhan Hongbin , Chen Xiaoyang , Lu Akang , Zha Shijiao
Published: November 2021

Nitrogen and phosphorus are commonly recognized as causing eutrophication in aquatic systems, and their transport in subsurface environments has also aroused great public attention. This research presented four natural clay minerals (NCMs) evaluated for their effectiveness of NH4 + and PO4 3- adsorption from wastewater. All the NCMs were fully characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), BET analysis, and adsorption kinetics and isotherms to better understand the adsorption mechanism-property relationship. The results show that the adsorption efficiency of the four NCMs for phosphate was better than that for ammonia nitrogen. The removal rate of phosphate was higher than 65%, generally in the range of 80%-90%, while the removal rate of ammonia nitrogen was less than 50%. The adsorption kinetic behavior followed the pseudo-second-order kinetic model. The ammonia nitrogen adsorption isotherm was in good agreement with the Freundlich isotherm equilibrium model, and the phosphate adsorption isotherm matched the Langmuir model. Among all the NCMs studied, bentonite (7.13 mg/g) and kaolinite (5.37 mg/g) showed higher adsorption capacities for ammonia nitrogen, while zeolite (0.21 mg/g) and attapulgite (0.17 mg/g) showed higher adsorption capacities for phosphate. This study provides crucial baseline knowledge for the adsorption of nitrogen and phosphate by different kinds of NCMs.
On Computation of Edge Degree-Based Banhatti Indices of a Certain Molecular Network
Authors: Tang Jiang-Hua , Abid Muhammad , Ali Kashif , Fahad Asfand , Chaudhry Muhammad Anwar , Qureshi Muhammad Imran , Liu Jia-Bao
Published: November 2021

Chemical graph theory deals with the basic properties of a molecular graph. In graph theory, we correlate molecular descriptors to the properties of molecular structures. Here, we compute some Banhatti molecular descriptors for water-soluble dendritic unimolecular polyether micelle. Our results prove to be very significant to understand the behaviour of water-soluble dendritic unimolecular polyether micelle as a drug-delivery agent.
Serum TNF‐α Level as a Possible Predictor of Inhibitor Levels in Severe Hemophilia A
Authors: Susanah Susi , Raspati Harry , Sari Nur Melani , Rakhmilla Lulu Eva , Sribudiani Yunia , Moestopo Octawyana , Sinaga Puspasari , Idjradinata Ponpon , Maskoen Ani Melani
Published: November 2021

Background. The development of factor VIII (FVIII) inhibitor in patients with hemophilia A (PWHA) is a great challenge for hemophilia care. Both genetic and environmental factors led to complications in PWHA. The development of inhibitory antibodies is usually induced by the immune response. Tumor necrosis factor α (TNF‐α), one of the cytokines, might contribute to its polymorphism. In this study, we investigated the clinical factors, level of serum TNF‐α, and polymorphism of c.−308G > A TNF − α gene in inhibitor development in severe PWHA. Methods. A cross‐sectional study was conducted among all PWHA in West Java province. The clinical parameters, FVIII, FVIII inhibitor, and serum TNF‐α level were assessed. The genotyping of −380G > A TNF‐α gene polymorphism was performed using polymerase chain reaction and Sanger sequencing. Results. Among the 258 PWHA, 216 (83.7%) were identified as severe PWHA. The FVIII inhibitor was identified in 90/216 (41.6%) of severe PWHA, consisting of 45 high‐titer inhibitors (HTI) and 45 low‐titer inhibitors (LTI). There was a significant correlation between serum TNF‐α level and the development of HTI (p = 0.043). The cutoff point of serum TNF‐α level, which can be used to differentiate between HTI and LTI, was 11.45 pg/mL. The frequency of FVIII replacement therapy was significant only in HTI of severe PWHA regarding serum TNF‐α level (p = 0.028). There is no correlation between polymorphisms of −380G > A TNF‐α gene and inhibitor development (p = 0.645). Conclusions. The prevalence of FVIII inhibitor in severe PWHA in West Java, Indonesia, was 41.6%. The frequency of replacement therapy is a risk factor for inhibitor development. Serum TNF‐α level might be used to differentiate between high and low inhibitor levels in severe hemophilia A, and this might support decision making regarding treatment options for inhibitor in severe hemophilia A.
mTORC1 Activation in Chx10‐Specific Tsc1 Knockout Mice Accelerates Retina Aging and Degeneration
Authors: Rao Yu-Qing , Zhou Yu-Tong , Zhou Wenchuan , Li Jia-Kai , Li Baojie , Li Jing
Published: November 2021

Age‐associated decline in retina function is largely responsible for the irreversible vision deterioration in the elderly population. It is also an important risk factor for the development of degenerative and angiogenic diseases. However, the molecular mechanisms involved in the process of aging in the retina remain largely elusive. This study investigated the role of mTORC1 signaling in aging of the retina. We showed that mTORC1 was activated in old‐aged retina, particularly in the ganglion cells. The role of mTORC1 activation was further investigated in Chx10-Cre;Tsc1fx/fx mouse (Tsc1‐cKO). Activation of mTORC1 was found in bipolar and some of the ganglion and amacrine cells in the adult Tsc1‐cKO retina. Bipolar cell hypertrophy and Müller gliosis were observed in Tsc1‐cKO since 6 weeks of age. The abnormal endings of bipolar cell dendritic tips at the outer nuclear layer resembled that of the old‐aged mice. Microglial cell activation became evident in 6‐week‐old Tsc1‐cKO. At 5 months, the Tsc1‐cKO mice exhibited advanced features of old‐aged retina, including the expression of p16Ink4a and p21, expression of SA‐β‐gal in ganglion cells, decreased photoreceptor cell numbers, decreased electroretinogram responses, increased oxidative stress, microglial cell activation, and increased expression of immune and inflammatory genes. Inhibition of microglial cells by minocycline partially prevented photoreceptor cell loss and restored the electroretinogram responses. Collectively, our study showed that the activation of mTORC1 signaling accelerated aging of the retina by both cell autonomous and nonautonomous mechanisms. Our study also highlighted the role of microglia cells in driving the decline in retina function.