Establishment of Outbreak Thresholds for Hepatitis A in South Africa Using Laboratory Surveillance, 2017–2020

As South Africa transitions from endemic to intermediate endemicity, hepatitis A surveillance needs strengthening to monitor trends in disease incidence and to identify outbreaks. We used passive laboratory-based surveillance data from the National Health Laboratory Services to calculate national hepatitis A incidence and to establish thresholds for outbreaks. Incidence was calculated by age and geographic location. The static threshold used two or three standard deviations (SDs) above the mean hepatitis A incidence in 2017–2019, and a cumulative summation (CuSum2) threshold used three SDs above the mean of the preceding seven months. These thresholds were applied to hepatitis A data for 2020. From 2017 to 2020, the mean incidence of hepatitis A IgM was 4.06/100,000 and ranged from 4.23 to 4.85/100,000 per year. Hepatitis A incidence was highest in the Western Cape province (WCP) (7.00–10.92/100,000 per year). The highest incidence was in the 1–9-year-olds. The incidence of hepatitis A in 2020 exceeded the static threshold in two districts of the WCP: Cape Winelands in January and Overberg district in August. The provincial incidence did not exceed the static and CuSum2 thresholds. District-level analysis using either threshold was sensitive enough to monitor trends and to alert district health authorities, allowing early outbreak responses.

Event-triggered discrete extended state observer–based model-free controller for quadrotor position and attitude trajectory tracking

In this article, an event-triggered discrete extended state observer–based model-free controller is developed for the position and attitude trajectory tracking of a quadrotor with uncertainties and external disturbances. The referred event-triggered discrete extended state observer–based model-free controller is composed of two event-triggered mechanisms, ultra-local model-based discrete extended state observer and proportional-derivative sub-controller. To reduce system output signal transmission, the event-triggered mechanism of output signal which owns dynamic and static threshold is designed. Based on event-triggered output signals, the discrete extended state observer is constructed to obtain the estimations of state values which are utilized as controller’s variables and to compensate for the lumped disturbances. The proportional-derivative sub-controller is adopted to guarantee the convergence of trajectory tracking error. To decrease control input signal transmission, the event-triggered mechanism of input signal that processes static threshold is constructed. Moreover, the stability analysis of overall quadrotor system with the proposed control strategy is investigated using Lyapunov theorem and the Zeno behavior is avoided. Finally, corresponding control scheme for quadrotor system is structured and the numerical comparative simulation and co-simulation experiment are given to demonstrate the effectiveness and performance of the proposed approach.

Adaptive Sparse Representation of Continuous Input for Tsetlin Machines Based on Stochastic Searching on the Line

This paper introduces a novel approach to representing continuous inputs in Tsetlin Machines (TMs). Instead of using one Tsetlin Automaton (TA) for every unique threshold found when Booleanizing continuous input, we employ two Stochastic Searching on the Line (SSL) automata to learn discriminative lower and upper bounds. The two resulting Boolean features are adapted to the rest of the clause by equipping each clause with its own team of SSLs, which update the bounds during the learning process. Two standard TAs finally decide whether to include the resulting features as part of the clause. In this way, only four automata altogether represent one continuous feature (instead of potentially hundreds of them). We evaluate the performance of the new scheme empirically using five datasets, along with a study of interpretability. On average, TMs with SSL feature representation use 4.3 times fewer literals than the TM with static threshold-based features. Furthermore, in terms of average memory usage and F1-Score, our approach outperforms simple Multi-Layered Artificial Neural Networks, Decision Trees, Support Vector Machines, K-Nearest Neighbor, Random Forest, Gradient Boosted Trees (XGBoost), and Explainable Boosting Machines (EBMs), as well as the standard and real-value weighted TMs. Our approach further outperforms Neural Additive Models on Fraud Detection and StructureBoost on CA-58 in terms of the Area Under Curve while performing competitively on COMPAS.

Secondary Crash Identification using Crowdsourced Waze User Reports

Secondary crashes are crashes that occur as a result of the nonrecurrent congestion originating from primary crashes, and always have a greater impact on safety and traffic than a single crash. A better understanding of secondary crashes would benefit traffic incident management, and this requires accurate identification of secondary crashes. This study explores using crowdsourced Waze user reports to identify secondary crashes. A network-based clustering algorithm is proposed to extract the primary crash cluster, including all user reports originating from the primary crash, and any crash that occurred within the cluster would be a secondary crash. This method works as a filter to select accurate primary–secondary relationships, thus precisely identifying secondary crashes. A case study is performed with crashes occurring from June to December 2019 on a 30-mi stretch of I-40 in Knoxville, TN. A static threshold method (crash duration and 10 mi) was used to preselect the potential primary–secondary crash pairs, and 75 out of 708 crashes were identified as potential secondary crashes. Based on the preselected primary–secondary crash pairs, 17 secondary crashes were obtained with the proposed method and the results were compared with one of the commonly used methods, the speed contour plot method. Though the proposed method captured fewer secondary crashes, it did identify several secondary crashes that could not be observed with the speed contour plot method. The results showed the applicability of the method and the potential of crowdsourced Waze user reports in secondary crash identification.

Comparative evaluation of the results of surgical treatment of open-angle glaucoma using an Ex-Press® P-200 filtration device and drainage device “anti-glaucoma implant A3”

Purpose. The article presents the results of a comparative analysis of the effectiveness of surgical treatment of open-angle glaucoma using the Ex-Press P-200 filtering device and the Anti-glaucoma A3 implant. Materials and methods. Using simple sequential sampling, 52 patients (59 eyes) were divided into 2 groups. The first group was implanted with Ex-Press P-200, the second with Anti-glaucoma implant A3. The follow-up period for patients ranged from 6 months to three years. At each visit, a standard ophthalmic examination was performed. For tonometry, the ICare TA01i portable non-contact tonometer was used. To assess the stabilization of the glaucoma process, we performed static (threshold) automatic perimetry using the Pericom perimeter and optical coherence tomography (OCT) of the optic nerve heads using a Spectralis HRA-OCT tomograph (Heidelberg Engineering). Conclusions. The implantation of devices of both types led to a persistent decrease in intraocular pressure, maintenance of visual functions, and stabilization of the glaucoma process. Intra- and postoperative complications corresponded to the nature of filtering procedures and did not have significant differences in the groups. However, cases of shunt erosion were noted only in the group with implanted Ex-Press devices.

Environmental Regulation Intensity, Foreign Direct Investment, and Green Technology Spillover—An Empirical Study

Many researchers have studied the relationships among heterogeneous foreign direct investment (FDI), environmental regulation, and green total factor productivity. However, no research has been done on how different types of FDI can result in green technology spillover under different levels of environmental regulation intensity. To address this research gap, in this paper, we build a static linear panel model, a static panel threshold model, and a dynamic panel threshold model to investigate the environmental regulatory threshold effect of labor-based FDI and capital-based FDI in terms of their green technology spillover. Based on the measurement of green total factor productivity (GTFP) of 36 industry sectors in China from 2003 to 2015, we first compare the threshold effects of environmental regulation on green technology spillover between labor-based FDI and capital-based FDI with a static linear model and a static threshold model. The results show that environmental regulation is unable to significantly promote the green technology spillover of labor-based FDI. However, intensifying environmental regulation can reduce the negative impact of labor-based FDI on GTFP. The effect of environmental regulation on green technology spillover of capital-based FDI is more complex. In the static linear model, environmental regulation can significantly promote the green technology spillover of capital-based FDI. In the static threshold model, the green technology spillover of capital-based FDI exists only when the environmental regulation intensity is sufficiently low or sufficiently high. Finally, the dynamic threshold model is adopted for robustness check. The results show when the environmental regulation intensity is higher than a threshold, both types of FDI can indeed result in green technology spillover. In short, our results prove that to ensure that FDI results in green technology spillover, it is necessary to continue to strengthen environmental regulation.

Macular sensitivity in patients with congenital stationary night-blindness

AimTo evaluate and correlate mean light sensitivity thresholds (MLST) in patients with congenital stationary night-blindness (CSNB) in comparison with healthy subjects using microperimetry (MP1).MethodsEleven patients with CSNB and 13 healthy subjects were compared. In all subjects, static threshold perimetry was performed using MP1 evaluating the central 6 mm of the retina. This central retinal area was divided into three rings through using the ETDRS grid algorithm with an innermost (1 mm), inner (3 mm) and outer ring (6 mm). The MLSTs were acquired in nine sectors of the ETDRS grid. A comparison of MLST was performed between both groups using a t-test (significance level p<0.005).ResultsA significant reduction of MLST in the fovea (innermost ring, 1 mm) was observed for patients with CSNB (7.2±3.90 dB) in comparison to healthy subjects (19.7±0.75; p<0.0001). Similarly, comparison of MLST in all other sectors (superior/inferior/temporal and nasal) within the inner and outer ring revealed a statistically significant reduction in patients with CSNB compared with healthy subjects (p<0.001).ConclusionsExamination of macular retinal sensitivity intensity using MP1 revealed for the first time a significant reduction of MLST within the central 6 mm of the retina in patients with CSNB compared with healthy subjects. This finding supports MP1 as an additional diagnostic tool when examining patients with retinal dysfunctions such as CSNB.