Unknown Route Research Articles

A Deep Learning Approach for Flight Delay Prediction Through Time-Evolving Graphs

Flight delay prediction has recently gained growing popularity due to the significant role it plays in efficient airline and airport operation. Most of the previous prediction works consider the single-airport scenario, which overlooks the time-varying spatial interactions hidden in airport networks. In this paper, the flight delay prediction problem is investigated from a network perspective (i.e., multi-airport scenario). To model the time-evolving and periodic graph-structured information in the airport network, a flight delay prediction approach based on the graph convolutional neural network (GCN) is developed in this paper. More specifically, regarding that GCN cannot take both delay time-series and time-evolving graph structures as inputs, a temporal convolutional block based on the Markov property is employed to mine the time-varying patterns of flight delays through a sequence of graph snapshots. Moreover, considering that unknown occasional air routes under emergency may result in incomplete graph-structured inputs for GCN, an adaptive graph convolutional block is embedded into the proposed method to expose spatial interactions hidden in airport networks. Through extensive experiments, it has been shown that the proposed approach outperforms benchmark methods with a satisfying accuracy improvement at the cost of acceptable execution time. The obtained results reveal that deep learning approach based on graph-structured inputs have great potentials in the flight delay prediction problem.

Factors Associated with Delayed Diagnosis among Patients with COVID-19 in Okinawa, Japan

The delayed presentation and diagnosis of COVID-19 can contribute to spread of the disease to others but can also cause severe conditions. This study examined factors associated with delayed diagnosis among patients with COVID-19 in Okinawa, Japan. We used the data from 7125 reported cases of people living in Okinawa prefecture with symptom onset between September 2020 and March 2021. The outcome variable was the number of days from symptom onset to diagnosis. The predictor variables included age, sex, occupation, residential area, presumed infection route, and the day of the week. Cox regression analysis was used to compare the outcome between categories for each predictor variable. The median number of days from onset to diagnosis was 3 days, with an interquartile range of 1 to 5 days. Significantly more time from onset to diagnosis was observed in patients in their 60s vs. those in their 20s (hazard ratio: 0.88; 95% confidence interval: 0.81–0.96); hospitality workers were compared to office workers (0.90; 0.83–0.97), patients with unknown infection routes to those with known infection routes (0.77; 0.70–0.84), and those with symptom onset on Sundays/national holidays to those with symptom onset on weekdays (0.90; 0.85–0.96).

Overnutrition Induced Cognitive Impairment: Insulin Resistance, Gut-Brain Axis, and Neuroinflammation.

Overnutrition-related obesity has become a worldwide epidemic, and its prevalence is expected to steadily rise in the future. It is widely recognized that obesity exerts negative impacts on metabolic disorders such as type 2 diabetes mellitus (T2DM) and cardiovascular diseases. However, relatively fewer reports exist on the impairment of brain structure and function, in the form of memory and executive dysfunction, as well as neurogenerative diseases. Emerging evidence indicates that besides obesity, overnutrition diets independently induce cognitive impairments via multiple mechanisms. In this study, we reviewed the clinical and preclinical literature about the detrimental effects of obesity or high-nutrition diets on cognitive performance and cerebral structure. We mainly focused on the role of brain insulin resistance (IR), microbiota-gut-brain axis, and neuroinflammation. We concluded that before the onset of obesity, short-term exposure to high-nutrition diets already blunted central responses to insulin, altered gut microbiome composition, and activated inflammatory mediators. Overnutrition is linked with the changes in protein expression in brain insulin signaling, leading to pathological features in the brain. Microbiome alteration, bacterial endotoxin release, and gut barrier hyperpermeability also occur to trigger mental and neuronal diseases. In addition, obesity or high-nutrition diets cause chronic and low-grade systematic inflammation, which eventually spreads from the peripheral tissue to the central nervous system (CNS). Altogether, a large number of unknown but potential routes interact and contribute to obesity or diet-induced cognitive impairment. The challenge for future research is to identify effective interventions involving dietary shifts and personalized therapy targeting the underlying mechanisms to prevent and improve cognition deficits.

Bioinspired Strain Sensor Using Multiwalled Carbon Nanotube/Polyvinyl Butyral/Nylon Cloth for Wireless Sensing Applications

The mushroom growth of wearable electronics greatly stimulates the demand of flexible strain sensors, and it makes sense to design a manufacturing method that avoids unknown biotoxicity, high-temperature treatment, and redundant technical route. Here, inspired by the geometry of slit receptor on spiders, we prepare a crack-based strain sensor using a facile, cost-effective and large-area-capable method. Conductive inks made of multiwalled carbon nanotubes (MWCNTs) and polyvinyl butyral (PVB) are drop onto nylon cloth, and then pre-stretched to 50% strain to generate long-range ordered and self-organized microcracks. Experimentally, the crack-based strain sensor delivers a superfast response time ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 31$ </tex-math></inline-formula> ms), balanced sensitivity and strain range (a gauge factor of 81.45 in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$15-50$ </tex-math></inline-formula> % strain range), and good reliability (>2500 cycles). These excellent sensing properties are attributed to the V-shaped microcrack structure that initiates significant resistance changes during repeated stretching/release. Meanwhile, the nylon substrate provides stable mechanical resilience to meet multiple stretching cycles. Combined with the wireless transmission system, the resistance signal measured by the strain sensor can be transmitted through Bluetooth and displayed in the mobile phone, realizing the real-time monitoring of human health and movements.

A Rare Alder-ene Cycloisomerization of 1,6-Allenynes.

Thermally induced cycloisomerization reactions of 1,6-allenynes gives α-methylene-γ-lactams via intramolecular Alder-ene reactions. The mechanism is supported by computational and deuterium labelling studies. This thermal, non-radical method enables the discovery of a hitherto unknown route that proceeds via a divergent mechanism distinct from the previous [2+2] cycloisomerization manifold.

Gaussian Support Vector Machine Algorithm Based Air Pollution Prediction

Air pollution is one of the major concerns considering detriments to human health. This type of pollution leads to several health problems for humans, such as asthma, heart issues, skin diseases, bronchitis, lung cancer, and throat and eye infections. Air pollution also poses serious issues to the planet. Pollution from the vehicle industry is the cause of greenhouse effect and CO2 emissions. Thus, real-time monitoring of air pollution in these areas will help local authorities to analyze the current situation of the city and take necessary actions. The monitoring process has become efficient and dynamic with the advancement of the Internet of things and wireless sensor networks. Localization is the main issue in WSNs; if the sensor node location is unknown, then coverage and power and routing are not optimal. This study concentrates on localization-based air pollution prediction systems for real-time monitoring of smart cities. These systems comprise two phases considering the prediction as heavy or light traffic area using the Gaussian support vector machine algorithm based on the air pollutants, such as PM2.5 particulate matter, PM10, nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and sulfur dioxide (SO2). The sensor nodes are localized on the basis of the predicted area using the meta-heuristic algorithms called fast correlation-based elephant herding optimization. The dataset is divided into training and testing parts based on 10 cross-validations. The evaluation on predicting the air pollutant for localization is performed with the training dataset. Mean error prediction in localizing nodes is 9.83 which is lesser than existing solutions and accuracy is 95%.

A Unique Sulfotransferase-Involving Strigolactone Biosynthetic Route in Sorghum.

LOW GERMINATION STIMULANT 1 (LGS1) plays an important role in strigolactones (SLs) biosynthesis and Striga resistance in sorghum, but the catalytic function remains unclear. Using the recently developed SL-producing microbial consortia, we examined the activities of sorghum MORE AXILLARY GROWTH1 (MAX1) analogs and LGS1. Surprisingly, SbMAX1a (cytochrome P450 711A enzyme in sorghum) synthesized 18-hydroxy-carlactonoic acid (18-hydroxy-CLA) directly from carlactone (CL) through four-step oxidations. The further oxidated product orobanchol (OB) was also detected in the microbial consortium. Further addition of LGS1 led to the synthesis of both 5-deoxystrigol (5DS) and 4-deoxyorobanchol (4DO). Further biochemical characterization found that LGS1 functions after SbMAX1a by converting 18-hydroxy-CLA to 5DS and 4DO possibly through a sulfonation-mediated pathway. The unique functions of SbMAX1 and LGS1 imply a previously unknown synthetic route toward SLs.

LC-IDS: Loci-Constellation-Based Intrusion Detection for Reconfigurable Wireless Networks

Detection accuracy of current machine-learning approaches to intrusion detection depends heavily on feature engineering and dimensionality-reduction techniques (e.g., variational autoencoder) applied to large datasets. For many use cases, a tradeoff between detection performance and resource requirements must be considered. In this paper, we propose Loci-Constellation-based Intrusion Detection System (LC-IDS), a general framework for network intrusion detection (detection of already known and previously unknown routing attacks) for reconfigurable wireless networks (e.g., vehicular ad hoc networks, unmanned aerial vehicle networks). We introduce the concept of ‘attack-constellation’, which allows us to represent all the relevant information for intrusion detection (misuse detection and anomaly detection) on a latent 2-dimensional space that arises naturally by considering the temporal structure of the input data. The attack/anomaly-detection performance of LC-IDS is analyzed through simulations in a wide range of network conditions. We show that for all the analyzed network scenarios, we can detect known attacks, with a good detection accuracy, and anomalies with low false positive rates. We show the flexibility and scalability of LC-IDS that allow us to consider a dynamic number of neighboring nodes and routing attacks in the ‘attack-constellation’ in a distributed fashion and with low computational requirements.

New Syphilis Cases in Older Adults, 2004-2019: An Analysis of Surveillance Data From South China.

Background: Sexual health among older adults is a major public health concern globally. The syphilis burden is increasing in older adults in China. This study aimed to describe factors associated with syphilis infection and diagnosis among older adults in China during a 16 year period.Methods: Using 16 years of data (2004–2019) from the syphilis case report system of Guangdong, China, we compared data from older adults (aged ≥50 years) with those from younger people (aged 15–49 years). We compared the two age group with the Chi-square test for difference, and Joinpoint regression models to assess the temporal trends.Results: During the study period, 242,115 new syphilis diagnoses were reported in older adults. The mean notification rate of new diagnoses was 64.1 per 100,000 population across the entire 16-year period, which significantly increased over time (average annual percent change [AAPC] 16.2%, 95% CI 13.7–18.7). Syphilis diagnoses increased significantly over time among less developed cities and older women. In 2019, compared with younger adults, newly diagnosed older adults were more likely to be male, native to reporting city, had unknown transmission routes, and were diagnosed late.Conclusion: Our findings call for an urgent need to deliver more targeted prevention interventions for older adults, such as strengthen awareness among health care providers, and integration of syphilis services and primary health care for older adults.

Endothelin-1 as a Mediator of Heme Oxygenase-1-Induced Stemness in Colorectal Cancer: Influence of p53.

Heme oxygenase-1 (HO-1) is an antioxidant protein implicated in tumor progression, metastasis, and resistance to therapy. Elevated HO-1 expression is associated with stemness in several types of cancer, although this aspect has not yet been studied in colorectal cancer (CRC). Using an in vitro model, we demonstrated that HO-1 overexpression regulates stemness and resistance to 5-FU treatment, regardless of p53. In samples from CRC patients, HO-1 and endothelin converting enzyme-1 (ECE-1) expression correlated significantly, and p53 had no influence on this result. Carbon monoxide (CO) activated the ECE-1/endothelin-1 (ET-1) pathway, which could account for the protumoral effects of HO-1 in p53 wild-type cells, as demonstrated after treatment with bosentan (an antagonist of both ETRA and ETRB endothelin-1 receptors). Surprisingly, in cells with a non-active p53 or a mutated p53 with gain-of-function, ECE-1-produced ET-1 acted as a protective molecule, since treatment with bosentan led to increased efficiency for spheres formation and percentage of cancer stem cells (CSCs) markers. In these cells, HO-1 could activate or inactivate certain unknown routes that could induce these contrary responses after treatment with bosentan in our cell model. However more research is warranted to confirm these results. Patients carrying tumors with a high expression of both HO-1 and ECE-1 and a non-wild-type p53 should be considered for HO-1 based-therapies instead of ET-1 antagonists-based ones.

Plastidial acyl carrier protein Δ9-desaturase modulates eicosapentaenoic acid biosynthesis and triacylglycerol accumulation in Phaeodactylum tricornutum.

SUMMARYThe unicellular marine diatom Phaeodactylum tricornutum accumulates up to 35% eicosapentaenoic acid (EPA, 20:5n3) and has been used as a model organism to study long chain polyunsaturated fatty acids (LC‐PUFA) biosynthesis due to an excellent annotated genome sequence and established transformation system. In P. tricornutum, the majority of EPA accumulates in polar lipids, particularly in galactolipids such as mono‐ and di‐galactosyldiacylglycerol. LC‐PUFA biosynthesis is considered to start from oleic acid (18:1n9). EPA can be synthesized via a series of desaturation and elongation steps occurring at the endoplasmic reticulum and newly synthesized EPA is then imported into the plastids for incorporation into galactolipids via an unknown route. The basis for the flux of EPA is fundamental to understanding LC‐PUFA biosynthesis in diatoms. We used P. tricornutum to study acyl modifying activities, upstream of 18:1n9, on subsequent LC‐PUFA biosynthesis. We identified the gene coding for the plastidial acyl carrier protein Δ9‐desaturase, a key enzyme in fatty acid modification and analyzed the impact of overexpression and knock out of this gene on glycerolipid metabolism. This revealed a previously unknown role of this soluble desaturase in EPA synthesis and production of triacylglycerol. This study provides further insight into the distinctive nature of lipid metabolism in the marine diatom P. tricornutum and suggests additional approaches for tailoring oil composition in microalgae.

From Alamut to Dadu: Jamāl al-Dīn’s Armillary Sphere on the Mongol Silk Roads

This article aims to shed light on a hitherto unknown transmission route of the astral sciences from Alamut to Dadu (Beijing). I argue that the huntianyi 渾天儀, an armillary sphere, which Jamāl al-Dīn dedicated to Qubilai in 1267, was designed in Alamut – the main stronghold of the Nizārī Ismāʿīlīs – on the grounds that the instrument was set to Alamut’s latitude. After its fall in 1256, the armillary sphere traversed the Mongol Silk Roads. The Dastūr al-munajjimīn, an Arabic work of the Nizārī Ismāʿīlīs, functions as the missing link in this West-to-East transmission.

Long Diagnostic Delay with Unknown Transmission Route Inversely Correlates with the Subsequent Doubling Time of Coronavirus Disease 2019 in Japan, February–March 2020

Long diagnostic delays (LDDs) may decrease the effectiveness of patient isolation in reducing subsequent transmission of coronavirus disease 2019 (COVID-19). This study aims to investigate the correlation between the proportion of LDD of COVID-19 patients with unknown transmission routes and the subsequent doubling time. LDD was defined as the duration between COVID-19 symptom onset and confirmation ≥6 days. We investigated the geographic correlation between the LDD proportion among 369 confirmed COVID-19 patients with symptom onset between the 9th and 11th week and the subsequent doubling time for 717 patients in the 12th–13th week among the six prefectures. The doubling time on March 29 (the end of the 13th week) ranged from 4.67 days in Chiba to 22.2 days in Aichi. Using a Pearson’s product-moment correlation (p-value = 0.00182) and multiple regression analyses that were adjusted for sex and age (correlation coefficient −0.729, 95% confidence interval: −0.923–−0.535, p-value = 0.0179), the proportion of LDD for unknown exposure patients was correlated inversely with the base 10 logarithm of the subsequent doubling time. The LDD for unknown exposure patients was correlated significantly and inversely with the subsequent doubling time.

Retrospective review of nicotine exposures in California from 2012 to 2018 and analysis of the impacts of e-cigarette regulations

ObjectivesTo review the association between US e-cigarette regulations and the number of reported nicotine exposures, and identify higher-risk productsDesignRetrospective review of de-identified medical records.SettingCaliforniaParticipantsCases reported to California Poison Control System...

Prevalence of HBV co-infection in HIV-positive population in China: a systematic review and Meta-analysis

Objective: To reveal the epidemiologic characteristics of hepatitis B virus (HBV) infection in HIV positive population in China. Methods: We collected research papers published from 2010 to 2019 on HBV co-infection in HIV positive population in China through literature retrieval, screening and quality evaluation. The Meta-analysis was conducted after extracting relevant data from the research papers meeting the inclusion criteria. Results: Twenty-seven studies were included with 69 816 samples. The pooled HBV infection rate in HIV positive population in China was 11.29%. The HBV co-infection rate was higher in the western China (10.73%) and southern China (14.18%), while lower in northern China (6.36%). The HBV infection rates were 11.22%, 12.76%, 9.58%, 11.32% and 10.34%, respectively, in HIV-positive population infected through blood or blood products transfusion, intravenous drug use, homosexual contact, heterosexual contact and unknown transmission routes. Population infected with HIV caused by mother-to-child transmission had the lowest HBV infection rate (2.87%). The HBV infection rate in HIV positive males was 1.29 times higher than that in HIV positive females in southern China. Conclusions: The HBV infection rate in HIV positive population is significantly higher than that in general population. More attention should be paid to the prevention and control of HBV co-infection in HIV positive population.

Comparison of the second and third waves of the COVID-19 pandemic in South Korea: Importance of early public health intervention

ObjectivesTo compare epidemiologic features of the second and third waves of the coronavirus disease 2019 (COVID-19) pandemic in South Korea. MethodsNationwide COVID-19 data were collected between 6 May and 30 December 2020. The degree of social activity was estimated using an Internet search trend analysis program for leisure-related keywords, including ‘eating-out’, ‘trip’ and ‘get directions’ (transportation). Demographics, transmission chains, case fatality rates, social activity levels and public health responses were compared between the second (13 August–18 September 2020) and third (4 November 2020–present) waves. ResultsIn comparison with the second wave, the third wave was characterized by delayed strengthening of social distancing policies (3 vs. 15 days), longer duration (36 vs. >56 days) and a higher case fatality rate (0.91% vs. 1.26%). There were significant differences in transmission chains between the second and third waves (P < 0.01). In comparison with the second wave, the proportion of local clusters (24.8% vs. 45.7%) was lower in the third wave, and personal contact transmission (38.5% vs. 25.9%) and unknown routes of transmission (23.5% vs. 20.8%) were higher in the third wave. ConclusionEarly and timely interventions with strengthened social distancing policies should be implemented to suppress and control the COVID-19 pandemic effectively.

Pediatric Cannabis Single-Substance Exposures Reported to the Michigan Poison Center From 2008-2019 After Medical Marijuana Legalization.

Legalization of medical and recreational cannabis is a major contributor to pediatric cannabis exposures. The trends and magnitude of pediatric cannabis exposures in Michigan after medical cannabis legalization in 2008 have not been assessed. To describe the temporal trends of pediatric cannabis exposures reported to the Michigan Poison Center (MiPC) after medical cannabis was legalized in 2008 and 1year after legalization of recreational cannabis in2018. Retrospective electronic chart review of pediatric (<18years old) single-substance cannabis exposures reported to the MiPC from January 1, 2008 to December 31, 2019. Routes of cannabis exposure were reported as ingestion, inhalation, and unknown. Types of ingested cannabis products were also documented. Between 2008 and 2019, 426 pediatric cannabis single exposures were reported. The median patient age was 6.0years (interquartile range 2-15years). Age distribution was bimodal. A total of 327 (76.8%) exposures were from cannabis ingestion, 79 (18.5%) from inhalation, 2 (0.5%) from both ingestion and inhalation, and 18 (4.2%) from unknown route. The doubling time for number of cases was 2.1years, and the total number of annual reported cases increased after 2016. Teenagers (13-17years) had the highest number of inhalational exposures, whereas young children (0-5years) had the highest number of ingestions. Single-substance pediatric cannabis exposures reported to the Michigan Poison Center increased after medical cannabis was legalized in 2008 through recreational legalization in2018.

A Structure Landmark-Based Radio Signal Mapping Approach for Sustainable Indoor Localization

Low cost and high reproducible is a key issue for sustainable location-based services. Currently, Wi-Fi fingerprinting based indoor positioning technology has been widely used in various applications due to the advantage of existing wireless network infrastructures and high positioning accuracy. However, the collection and construction of signal radio map (a basis for Wi-Fi fingerprinting-based localization) is a labor-intensive and time-cost work, which limit their practical and sustainable use. In this study, an indoor signal mapping approach is proposed, which extracts fingerprints from unknown signal mapping routes to construct the radio map. This approach employs special indoor spatial structures (termed as structure landmarks) to estimate the location of fingerprints extracted from mapping routes. A learning-based classification model is designed to recognize the structure landmarks along a mapping route based on visual and inertial data. A landmark-based map matching algorithm is also developed to attach the recognized landmarks to a map and to recover the location of the mapping route without knowing its initial location. Experiment results showed that the accuracy of landmark recognition model is higher than 90%. The average matching accuracy and location error of signal mapping routes is 96% and 1.2 m, respectively. By using the constructed signal radio map, the indoor localization error of two algorithms can reach an accuracy of 1.6 m.

Exit choice during evacuation is influenced by both the size and proportion of the egressing crowd

It is unclear how building occupants use information about the social and built environment when choosing an egress route during emergency evacuation. Conflicting tendencies have been previously reported: to follow the crowd, to avoid congestion, and to avoid unknown egress routes alone. We hypothesize that these tendencies depend on an interaction between social influence and the affordances (opportunities for egress) of the built environment. In three virtual reality (VR) experiments (each N=15), we investigated how social influence interacts with the affordances of available exits to determine exit choice. Participants were immersed in a crowd of virtual humans walking to the left or right exit and were asked to walk to one of the exits. Experiment 1 tested the role of social influence by manipulating both the proportion of the crowd walking toward one exit point (Crowd Proportion of 0 to 100%, in 10% increments) and the absolute number of virtual humans going to the exit point (Crowd Size of 10 or 20). Experiment 2 tested the role of affordances by introducing two visible exit doors (1 m width) in a closed room, and following the same protocol. Experiment 3 tested larger exit doors (2 m width) that afford rapid egress for more people. In the small crowd, participants were increasingly likely to follow the majority as its proportion increased. In the large crowd, however, participants tended to avoid the more crowded exit if the doors were narrow (Experiment 2), but not if the doors were wide (Experiment 3). Participants tended to follow a 100% majority in all experiments, thereby avoiding going to an exit alone. We propose that the dynamics of exit choice can be understood in terms of competition between alternative egress routes: the attraction of an exit increases with the proportion of the crowd moving toward it, becoming dominant at 100%, but decreases with the absolute number in the crowd moving toward it, relative to the exit’s affordance for egress.

Viral infections and implications for male reproductive health.

Viral infections have haunted humankind since times immemorial. Overpopulation, globalization, and extensive deforestation have created an ideal environment for a viral spread with unknown and multiple shedding routes. Many viruses can infect the male reproductive tract, with potential adverse consequences to male reproductive health, including infertility and cancer. Moreover, some genital tract viral infections can be sexually transmitted, potentially impacting the resulting offspring's health. We have summarized the evidence concerning the presence and adverse effects of the relevant viruses on the reproductive tract (mumps virus, human immunodeficiency virus, herpes virus, human papillomavirus, hepatitis B and C viruses, Ebola virus, Zika virus, influenza virus, and coronaviruses), their routes of infection, target organs and cells, prevalence and pattern of virus shedding in semen, as well as diagnosis/testing and treatment strategies. The pathophysiological understanding in the male genital tract is essential to assess its clinical impact on male reproductive health and guide future research.