Analyzing Performance of YOLOx for Detecting Vehicles in Bad Weather Conditions

Recent advancements in computer vision technology, developments in sensors and sensor-collecting approaches, and the use of deep and transfer learning approaches have excelled in the development of autonomous vehicles. On-road vehicle detection has become a task of significant importance, especially due to exponentially increasing research on autonomous vehicles during the past few years. With high-end computing resources, a large number of deep learning models have been trained and tested for on-road vehicle detection recently. Vehicle detection may become a challenging process especially due to varying light and weather conditions like night, snow, sand, rain, foggy conditions, etc. In addition, vehicle detection should be fast enough to work in real time. This study investigates the use of the recent YOLO version, YOLOx, to detect vehicles in bad weather conditions including rain, fog, snow, and sandstorms. The model is tested on the publicly available benchmark dataset DAWN containing images containing four bad weather conditions, different illuminations, background, and number of vehicles in a frame. The efficacy of the model is evaluated in terms of precision, recall, and mAP. The results exhibit the better performance of YOLOx-s over YOLOx-m and YOLOx-l variants. YOLOx-s has 0.8983 and 0.8656 mAP for snow and sandstorms, respectively, while its mAP for rain and fog is 0.9509 and 0.9524, respectively. The performance of models is better for snow and foggy weather than rainy weather sandstorms. Further experiments indicate that enhancing image quality using multiscale retinex improves YOLOx performance.

Nested Bee Hive: A Conceptual Multilayer Architecture for 6G in Futuristic Sustainable Smart Cities

Several smart city ideas are introduced to manage various problems caused by overpopulation, but the futuristic smart city is a concept based on dense and artificial-intelligence-centric cities. Thus, massive device connectivity with huge data traffic is expected in the future where communication networks are expected to provide ubiquity, high quality of service, and on-demand content for a large number of interconnected devices. The sixth-generation (6G) network is considered the problem-solving network of futuristic cities, with huge bandwidth and low latency. The expected 6G of the radio access network is based on terahertz (THz) waves with the capability of carrying up to one terabit per second (Tbps). THz waves have the capability of carrying a large amount of data but these waves have several drawbacks, such as short-range and atmospheric attenuation. Hence, these problems can introduce complications and hamper the performance of the 6G network. This study envisions futuristic smart cities using 6G and proposes a conceptual terrestrial network (TN) architecture for 6G. The nested Bee Hive is a scalable multilayer architecture designed to meet the needs of futuristic smart cities. Moreover, we designed the multilayer network infrastructure while considering the expectations from a network of futuristic smart cities and the complications of THz waves. Extensive simulations are performed using different pathfinding algorithms in the 3D multilayer domain to evaluate the performance of the proposed architecture and set the dynamics of futuristic communication of 6G.

Empirical Overview of Benchmark Datasets for Geomagnetic Field-Based Indoor Positioning

Indoor positioning and localization have been regarded as some of the most widely researched areas during the last decade. The wide proliferation of smartphones and the availability of fast-speed internet have initiated several location-based services. Concerning the importance of precise location information, many sensors are embedded into modern smartphones. Besides Wi-Fi positioning, a rich variety of technologies have been introduced or adopted for indoor positioning such as ultrawideband, infrared, radio frequency identification, Bluetooth beacons, pedestrian dead reckoning, and magnetic field, etc. However, special emphasis is put on infrastructureless approaches like Wi-Fi and magnetic field-based positioning, as they do not require additional infrastructure. Magnetic field positioning is an attractive solution for indoors; yet lack of public benchmarks and selection of suitable benchmarks are among the big challenges. While several benchmarks have been introduced over time, the selection criteria of a benchmark are not properly defined, which leads to positioning results that lack generalization. This study aims at analyzing various public benchmarks for magnetic field positioning and highlights their pros and cons for evaluation positioning algorithms. The concept of DUST (device, user, space, time) and DOWTS (dynamicity, orientation, walk, trajectory, and sensor fusion) is introduced which divides the characteristics of the magnetic field dataset into basic and advanced groups and discusses the publicly available datasets accordingly.

Radiological management of postoperative lymphorrhea

PURPOSE

Postoperative lymphorrhea can occur after different surgical procedures and may prolong the hospital stay due to the need for specific treatment. In this work, the therapeutic significance of the radiological management of postoperative lymphorrhea was assessed and illustrated.

METHOD

A standardized search of the literature was performed in PubMed applying the Medical Subject Headings (MeSH) term "lymphangiography." For the review, the inclusion criterion was "studies with original data on Lipiodol-based Conventional Lymphangiography (CL) with subsequent Percutaneous Lymphatic Intervention (PLI)." Different exclusion criteria were defined (e.g., studies with <15 patients). The collected data comprised of clinical background and indications, procedural aspects and types of PLI, and outcomes. In the form of a pictorial essay, each author illustrated a clinical case with CL and/or PLI.

RESULTS

Seven studies (corresponding to evidence level 4 [Oxford Centre for Evidence-Based Medicine]) accounting for 196 patients were included in the synthesis and analysis of data. Preceding surgery resulting in postoperative lymphorrhea included different surgical procedures such as extended oncologic surgery or vascular surgery. Central (e.g., chylothorax) and peripheral (e.g., lymphocele) types of postoperative lymphorrhea with a drainage volume of 100-4000 ml/day underwent CL with subsequent PLI. The intervals between "preceding surgery and CL" and between "CL and PLI" were 2-330 days and 0-5 days, respectively. CL was performed before PLI to visualize the lymphatic pathology (e.g., leakage point or inflow lymph ducts), applying fluoroscopy, radiography, and/or computed tomography (CT). In total, seven different types of PLI were identified: (1) thoracic duct (or thoracic inflow lymph duct) embolization, (2) thoracic duct (or thoracic inflow lymph duct) maceration, (3) leakage point direct embolization, (4) inflow lymph node interstitial embolization, (5) inflow lymph duct (other than thoracic) embolization, (6) inflow lymph duct (other than thoracic) maceration, and (7) transvenous retrograde lymph duct embolization. CL-associated and PLI-associated technical success rates were 97-100% and 89-100%, respectively. The clinical success rate of CL and PLI was 73-95%. CL-associated and PLI-associated major complication rates were 0-3% and 0-5%, respectively. The combined CL- and PLI-associated 30-day mortality rate was 0%, and the overall mortality rate was 3% (corresponding to six patients). In the pictorial essay, the spectrum of CL and/or PLI was illustrated.

CONCLUSION

The radiological management of postoperative lymphorrhea is feasible, safe, and effective. Standardized radiological treatments embedded in an interdisciplinary concept are a step towards improving outcomes.

Engineered ionizable lipid nanoparticles for targeted delivery of RNA therapeutics into different types of cells in the liver

Ionizable lipid nanoparticles (LNPs) have been widely used for in vivo delivery of RNA therapeutics into the liver. However, a main challenge remains to develop LNP formulations for selective delivery of RNA into certain types of liver cells, such as hepatocytes and liver sinusoidal endothelial cells (LSECs). Here, we report the engineered LNPs for the targeted delivery of RNA into hepatocytes and LSECs. The effects of particle size and polyethylene glycol-lipid content in the LNPs were evaluated for the hepatocyte-specific delivery of mRNA by ApoE-mediated cellular uptake through low-density lipoprotein receptors. Targeted delivery of RNA to LSECs was further investigated using active ligands. Incorporation of mannose allowed the selective delivery of RNA to LSECs, while minimizing the unwanted cellular uptake by hepatocytes. These results demonstrate that engineered LNPs have great potential for the cell type-specific delivery of RNA into the liver and other tissues.

Enhancing Performance of Magnetic Field Based Indoor Localization Using Magnetic Patterns from Multiple Smartphones

Wide expansion of smartphones triggered a rapid demand for precise localization that can meet the requirements of location-based services. Although the global positioning system is widely used for outdoor positioning, it cannot provide the same accuracy for the indoor. As a result, many alternative indoor positioning technologies like Wi-Fi, Bluetooth Low Energy (BLE), and geomagnetic field localization have been investigated during the last few years. Today smartphones possess a rich variety of embedded sensors like accelerometer, gyroscope, and magnetometer that can facilitate estimating the current location of the user. Traditional geomagnetic field-based fingerprint localization, although it shows promising results, it is limited by the fact that various smartphones have embedded magnetic sensors from different manufacturers and the magnetic field strength that is measured from these smartphones vary significantly. Consequently, the localization performance from various smartphones is different even when the same localization approach is used. So devising an approach that can provide similar performance with various smartphones is a big challenge. Contrary to previous works that build the fingerprint database from the geomagnetic field data of a single smartphone, this study proposes using the geomagnetic field data collected from multiple smartphones to make the geomagnetic field pattern (MP) database. Many experiments are carried out to analyze the performance of the proposed approach with various smartphones. Additionally, a lightweight threshold technique is proposed that can detect user motion using the acceleration data. Results demonstrate that the localization performance for four different smartphones is almost identical when tested with the database made using the magnetic field data from multiple smartphones than that of which considers the magnetic field data from only one smartphone. Moreover, the performance comparison with previous research indicates that the overall performance of smartphones is improved.

Catastrophic factors involved in road accidents: Underlying causes and descriptive analysis

South Korea is ranked as 4th among 34 nations of the Organization for Economic Cooperation and Development with 102 deaths in road accidents per one million population. This paper aims to investigate the factors associated with road accidents in South Korea. The rainfall data of the Korea Meteorological Administration and road accidents data of Traffic Accident Analysis System of Korea Road Traffic Authority is analyzed for this purpose. In this connection, multivariate regression analysis and ratio analysis with the descriptive analysis are performed to uncover the catastrophic factors involved. In turn, the results reveal that traffic volume is the leading factor in road accidents. The limited road extension of 1.47% compared to the 4.14% per annum growth of the vehicles is resulting in road accidents at such a large scale. The increasing proportion of passenger cars accelerate road accidents as well. 56% of accidents occur by the infringement of safety driving violations. The drivers with higher driving experience tend to have a higher accident ratio. The collected data is analyzed in terms of gender, driver experience, type of violations and accidents as well as the associated time of the accidents when they happen. The results indicate that 36.29% and 53.01% of accidents happen by male drivers in the day and night time, respectively. 29.15% of crashes happen due to safety infringement and violations of 41 to 60 years old drivers. The results demonstrate that population density is associated with the accidents frequency and lower density results in an increased number of accidents. The necessity of the state-of-the-art regulations to govern the urban road traffic is beyond dispute, and it becomes even more crucial for citizens’ relief since in our daily lives road accidents are getting more diverse.

Floor Identification Using Magnetic Field Data With Smartphone Sensors

Floor identification plays a key role in multi-story indoor positioning and localization systems. Current floor identification systems rely primarily on Wi-Fi signals and barometric pressure data. Barometric systems require installation of additional standalone sensors to perform floor identification. Wi-Fi systems, on the other hand, are vulnerable to the dynamic environment and adverse effects of path loss, shadowing, and multipath fading. In this paper, we take advantage of a pervasive magnetic field to compensate for the limitations of these systems. We employ smartphone sensors to make the proposed scheme infrastructure free and cost-effective. We use smartphone magnetic sensors to identify the floors in a multi-story building with improved accuracy. Floor identification is performed with user activities of normal walking, call listening, and phone swinging. Various machine learning techniques are leveraged to identify user activities. Extensive experiments are performed to evaluate the proposed magnetic-data-based floor identification scheme. Additionally, the impact of device heterogeneity on floor identification is investigated using Samsung Galaxy S8, LG G6, and LG G7 smartphones. Research results demonstrate that the magnetic floor identification outperforms barometric and Wi-Fi-enabled floor detection techniques. A floor change module is incorporated to further enhance the accuracy of floor identification.

Abstract P2-06-01: Molecular characterization of human malignant phyllodes tumors reveals potential targeted approaches

Malignant phyllodes tumor (MPT) which belong to the fibroepithelial neoplasm spectrum is a rare type of breast malignancy, and currently there is no effective targeted approach available for MPT. In this study, we tried to identify key genomic alterations and biologic pathways in MPT by whole exome and RNA sequencing of nine MPT tissues. Whole exome sequencing revealed somatic alterations in EGFR, MED12, PIK3CA, PIK3R1, PDGFRA, PDGFRB, PTEN, and TP53. Transcriptome sequencing showed dysregulation of ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling in MPTs when compared to normal breast or invasive breast cancer tissues. Based on the transcriptome profiles, the MPTs were classified into two subtypes; fibrous subtype with upregulation of stromal genes such as collagens and epithelial subtype with upregulation of E-cadherin and Claudins. The molecular classification of fibrous and epithelial subtypes was validated in 28 paraffin-embedded MPT tissues. The fibrous subtype showed higher mitotic index and increased risk for recurrence when compared to the epithelial subtype. We established a patient-derived xenograft model from one fibrous subtype MPT which harbored somatic mutation in PIK3R1 and PDGFRB. In that model, targeted treatment against PIK3CA/mTOR and PDGFR pathways effectively suppressed the tumor growth in vivo. Our data provide insights on the biologic understanding of MPT and suggest a clinically relevant molecular classification. Furthermore, we show that developing effective targeted approaches in MPT can be possible with genomic profiles and patient-derived xenograft models. The clinical efficacy of targeting PDGFR and PIK3CA/mTOR pathways in MPT should be tested in future clinical trials.

Citation Format: Moon H-G, Yun J, Hong BS, Lee E, Lee H-B, Han W, Kim J-I, Noh D-Y, Heo W, Hur S, Kang W, Lee C. Molecular characterization of human malignant phyllodes tumors reveals potential targeted approaches [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-06-01.

LOCALI: Calibration-Free Systematic Localization Approach for Indoor Positioning

Recent advancements in indoor positioning systems are based on infrastructure-free solutions, aimed at improving the location accuracy in complex indoor environments without the use of specialized resources. A popular infrastructure-free solution for indoor positioning is a calibration-based positioning, commonly known as fingerprinting. Fingerprinting solutions require extensive and error-free surveys of environments to build radio-map databases, which play a key role in position estimation. Fingerprinting also requires random updates of the database, when there are significant changes in the environment or a decrease in the accuracy. The calibration of the fingerprinting database is a time-consuming and laborious effort that prevents the extensive adoption of this technique. In this paper, we present a systematic LOCALIzation approach, “LOCALI”, for indoor positioning, which does not require a calibration database and extensive updates. The LOCALI exploits the floor plan/wall map of the environment to estimate the target position by generating radio maps by integrating path-losses over certain trajectories in complex indoor environments, where triangulation using time information or the received signal strength level is highly erroneous due to the fading effects caused by multi-path propagation or absorption by environmental elements or varying antenna alignment. Experimental results demonstrate that by using the map information and environmental parameters, a significant level of accuracy in indoor positioning can be achieved. Moreover, this process requires considerably lesser effort compared to the calibration-based techniques.

Endogenous Retroelements and the Host Innate Immune Sensors

The ability to distinguish between self and nonself is the fundamental basis of the immune system in all organisms. The conceptual distinction between self and nonself, however, breaks down when it comes to endogenous retroviruses and other retroelements. While some retroelements retain the virus-like features including the capacity to replicate and reinvade the host genome, most have become inactive through mutations or host epigenetic silencing. And yet, accumulating evidence suggests that endogenous retroelements, both active and inactive, play important roles not only in pathogenesis of immune disorders, but also in proper functioning of the immune system. This review discusses the recent development in our understanding of the interaction between retroelements and the host innate immune system. In particular, it focuses on the impact of retroelement transcripts on the viral RNA sensors such as Toll-like receptors, RIG-I-like receptors, protein kinase R, and the inflammasomes.

MR/GI/1 queues by positively correlated arrival stream

The effects of dependencies (such as association) in the arrival process to a single server queue on mean queue lengths and mean waiting times are studied. Markov renewal arrival processes with a particular transition matrix for the underlying Markov chain are used which allow us to change dependency properties without at the same time changing distributional conditions. It turns out that correlations do not seem to be pure effects, and three main factors are studied: (a) differences in the mean interarrival times in the underlying Markov renewal process, (b) intensity in the Markov renewal jump process, (c) variability in the point processes underlying the Markov renewal process. It is shown that the mean queue length can be made arbitrarily large in the class of queues with the same interarrival distributions and the same service time distributions (with fixed smaller than one traffic intensity), by making (a) large enough and (b) small enough. The existence of the moments of interest is confirmed and some stochastic comparison results for actual waiting times are shown.

Unusual cutaneous features associated with a heterozygous gain-of-function mutation in IFIH1: overlap between Aicardi-Goutières and Singleton-Merten syndromes

Cutaneous lesions described as chilblain lupus occur in the context of familial chilblain lupus or Aicardi-Goutières syndrome. To date, seven genes related to Aicardi-Goutières syndrome have been described. The most recently described encodes the cytosolic double-stranded RNA receptor IFIH1 (also known as MDA5), a key component of the antiviral type I interferon-mediated innate immune response. Enhanced type I interferon signalling secondary to gain-of-function mutations in IFIH1 can result in a range of neuroinflammatory phenotypes including classical Aicardi-Goutières syndrome. It is of note that none of the patients with a neurological phenotype so far described with mutations in this gene was reported to demonstrate cutaneous involvement. We present a family segregating a heterozygous pathogenic mutation in IFIH1 showing dermatological involvement as a prominent feature, variably associated with neurological disturbance and premature tooth loss. All three affected individuals exhibited increased expression of interferon-stimulated genes in whole blood, and the mutant protein resulted in enhanced interferon signalling in vitro, both in the basal state and following ligand stimulation. Our results further extend the phenotypic spectrum associated with mutations in IFIH1, indicating that the disease can be confined predominantly to the skin, while also highlighting phenotypic overlap with both Aicardi-Goutières syndrome and Singleton-Merten syndrome.

Homoisoflavanone prevents mast cell activation and allergic responses by inhibition of Syk signaling pathway

BACKGROUND

Mast cells play important roles in allergic inflammatory responses because they produce leukotrienes (LTs), prostaglandins (PGs), and a variety of inflammatory cytokines. Thus, pharmacological interventions for allergies have focused on inhibiting mast cell activation. Homoisoflavanone (HIF), isolated from Cremastra appendiculata Makino, has anti-angiogenic activities; however, its effects on allergic reactions have not been determined. The aim of this study was to assess the inhibitory effects of HIF on mast cell activation, which is critical for anti-allergic reaction and the underlying mechanisms.

METHODS

Enzyme-linked immunosorbent assays, quantitative real-time PCR, western blot analyses, and degranulation assay were performed to measure pro-inflammatory and allergic mediators in PMA/A23187- or IgE/antigen-stimulated mouse bone marrow-derived mast cells (BMMCs), HMC-1, RBL-1, or human PBMC-derived mast cells treated with or without HIF. The anti-allergic effects of HIF were determined in mouse models using dinitrophenol-immunoglobulin E-induced passive cutaneous anaphylaxis (PCA) and compound 48/80-induced ear swelling.

RESULTS

Homoisoflavanone down-regulated PGD2 , LTB4 , and LTC4 production and inhibited the production of pro-inflammatory cytokines, such as interleukin-6 and tumor necrosis factor-α in PMA/A23187- or IgE/antigen-stimulated mast cells. The molecular mechanisms by which HIF caused these inhibitory effects were determined to be the inactivation of spleen tyrosine kinase (Syk) signaling and the concurrent suppression of cPLA2 . HIF inhibited IgE-mediated PCA and compound 48/80-induced ear swelling in mouse.

CONCLUSIONS

Homoisoflavanone inhibited mast cell activation through the suppression of Syk pathway together with the inhibition of cPLA2 . Thus, it might be a good candidate molecule for allergic diseases.

Passive Wireless MEMS Microphones for Biomedical Applications

This paper introduces passive wireless telemetry based operation for high frequency acoustic sensors. The focus is on the development, fabrication, and evaluation of wireless, batteryless SAW-IDT MEMS microphones for biomedical applications. Due to the absence of batteries, the developed sensors are small and as a result of the batch manufacturing strategy are inexpensive which enables their utilization as disposable sensors. A pulse modulated surface acoustic wave interdigital transducer (SAW-IDT) based sensing strategy has been formulated. The sensing strategy relies on detecting the ac component of the acoustic pressure signal only and does not require calibration. The proposed sensing strategy has been successfully implemented on an in-house fabricated SAW-IDT sensor and a variable capacitor which mimics the impedance change of a capacitive microphone. Wireless telemetry distances of up to 5 centimeters have been achieved. A silicon MEMS microphone which will be used with the SAW-IDT device is being microfabricated and tested. The complete passive wireless sensor package will include the MEMS microphone wire-bonded on the SAW substrate and interrogated through an on-board antenna. This work on acoustic sensors breaks new ground by introducing high frequency (i.e., audio frequencies) sensor measurement utilizing SAW-IDT sensors. The developed sensors can be used for wireless monitoring of body sounds in a number of different applications, including monitoring breathing sounds in apnea patients, monitoring chest sounds after cardiac surgery, and for feedback sensing in compression (HFCC) vests used for respiratory ventilation. Another promising application is monitoring chest sounds in neonatal care units where the miniature sensors will minimize discomfort for the newborns.