Ino2, activator of yeast phospholipid biosynthetic genes, interacts with basal transcription factors TFIIA and Bdf1.

Binding of general transcription factors TFIID and TFIIA to basal promoters is rate-limiting for transcriptional initiation of eukaryotic protein-coding genes. Consequently, activator proteins interacting with subunits of TFIID and/or TFIIA can drastically increase the rate of initiation events. Yeast transcriptional activator Ino2 interacts with several Taf subunits of TFIID, among them the multifunctional Taf1 protein. In contrast to mammalian Taf1, yeast Taf1 lacks bromodomains which are instead encoded by separate proteins Bdf1 and Bdf2. In this work, we show that Bdf1 not only binds to acetylated histone H4 but can also be recruited by Ino2 and unrelated activators such as Gal4, Rap1, Leu3 and Flo8. An activator-binding domain was mapped in the N-terminus of Bdf1. Subunits Toa1 and Toa2 of yeast TFIIA directly contact sequences of basal promoters and TFIID subunit TBP but may also mediate the influence of activators. Indeed, Ino2 efficiently binds to two separate structural domains of Toa1, specifically with its N-terminal four-helix bundle structure required for dimerization with Toa2 and its C-terminal ß-barrel domain contacting TBP and sequences of the TATA element. These findings complete the functional analysis of yeast general transcription factors Bdf1 and Toa1 and identify them as targets of activator proteins.

Bilateral or unilateral tubo-ovarian abscess: exploring its clinical significance.

OBJECTIVES: To assess the characteristics of patients with unilateral and bilateral tubo-ovarian abscess (TOA). METHODS: Women diagnosed with TOA during 2003-2017 were included in this retrospective cohort study. TOA was diagnosed using sonography or computerized tomography and clinical criteria, or by surgical diagnosis. Demographics, sonographic data, clinical treatment, surgical treatment, and post-operative information were retrieved. RESULTS: The study cohort included 144 women who met the inclusion criteria, of whom 78 (54.2%) had unilateral TOA and 66 (45.8%) had bilateral TOA. Baseline characteristics were not different between the groups. There was a statistical trend that women with fewer events of previous PID were less likely to have with bilateral TOA (75.3% vs. 64.1%, respectively; p = 0.074). Women diagnosed with bilateral TOA were more likely to undergo surgical treratment for bilateral salpingo-oophorectomy compared to unilateral TOA (61.5% vs. 42.3%, respectively; p = 0.04). There was no difference in maximum TOA size between groups. CONCLUSIONS: This study detected a trend toward increased need for surgical treatment in women diagnosed with bilateral TOA. These findings may contribute to determining the optimal medical or surgical treatment, potentially leading to a decrease in the duration of hospitalization, antibiotic exposure, and resistance. However, it is important to acknowledge that the results of the current study are limited, and further research is warranted to validate these potential outcomes.

The role of systemic immune inflammation index in predicting treatment success in tuboovarian abscesses.

PURPOSE: The aim of this study was to determine the predictability of the systemic immune inflammation index (SII) on the response to medical treatment in tubo-ovarian abscess (TOA). METHODS: 296 patients with TOA in a tertiary center were enrolled in the study. Patients were divided into two groups: Group1 (n = 165) included patients in whom medical treatment was successful, and Group2 (n = 131) included patients in whom surgery was required. Demographic, sonographic and laboratory findings were compared between groups. SII was calculated using peripheral blood parameters [SII = (platelets ∗ neutrophils)/lymphocytes]. RESULTS: Age, BMI, gravida, parity, smoking and menopausal status, CRP levels of patients were similar in both groups (p > 0.05). Mass size (4.398 ± 0.306 vs 7.683 ± 0.689, p < 0.001), white blood cell (WBC) (8685.08 ± 3981.98 vs 9994.35 ± 4468.024, p = 0.008), Hb (12.18 ± 1.65 vs 11.68 ± 1.65, p = 0.010), platelet to lymphocyte ratio (PLR) (151.26 ± 74.83 vs 230.77 ± 140.25, p < 0.001), neutrophil to lymphocyte ratio (NLR) (4.21 ± 3.27 vs 6.07 ± 6.6, p = 0.003), monocyte to lymphocyte ratio (MLR) (0.300 ± 0.177 vs 0.346 ± 0.203, p = 0.041) and SII (1014.18 ± 781.71 vs 2094.088 ± 2117.58, p < 0.001) were statistically higher in group 2. ROC Analysis was used to determine the predictability of the variables and PLR (AUC = 0.718, p < 0.001), NLR (AUC = 0.593, p = 0.593), MLR (AUC = 0.576, p = 0.024), SII (AUC = 0.723, p < 0.001) and size of mass (AUC = 0.670, p < 0.001) were found to be significant. The SII, size of mass and bilateral involvement of adnexa were found to be the strongest prognostic factors for surgical intervention (OR:1.004 (1.002-1.005), OR:1.018 (1.010-1.027), OR:3.397 (1.338-8.627); p < 0.001, p < 0.001, p = 0.010 resspectively). CONCLUSION: SII, size of mass and bilaterality can be used to predict medical treatment success in patients with TOA.

Underwater Wireless Sensor Networks with RSSI-Based Advanced Efficiency-Driven Localization and Unprecedented Accuracy.

Deep-sea object localization by underwater acoustic sensor networks is a current research topic in the field of underwater communication and navigation. To find a deep-sea object using underwater wireless sensor networks (UWSNs), the sensors must first detect the signals sent by the object. The sensor readings are then used to approximate the object's position. A lot of parameters influence localization accuracy, including the number and location of sensors, the quality of received signals, and the algorithm used for localization. To determine position, the angle of arrival (AOA), time difference of arrival (TDoA), and received signal strength indicator (RSSI) are used. The UWSN requires precise and efficient localization algorithms because of the changing underwater environment. Time and position are required for sensor data, especially if the sensor is aware of its surroundings. This study describes a critical localization strategy for accomplishing this goal. Using beacon nodes, arrival distance validates sensor localization. We account for the fact that sensor nodes are not in perfect temporal sync and that sound speed changes based on the medium (water, air, etc.) in this section. Our simulations show that our system can achieve high localization accuracy by accounting for temporal synchronisation, measuring mean localization errors, and forecasting their variation. The suggested system localization has a lower mean estimation error (MEE) while using RSSI. This suggests that measurements based on RSSI provide more precision and accuracy during localization.

Wideband TDoA Positioning Exploiting RSS-Based Clustering.

The accuracy of radio-based positioning is heavily influenced by a dense multipath (DM) channel, leading to poor position accuracy. The DM affects both time of flight (ToF) measurements extracted from wideband (WB) signals-specifically, if the bandwidth is below 100 MHz-as well as received signal strength (RSS) measurements, due to the interference of multipath signal components onto the information-bearing line-of-sight (LoS) component. This work proposes an approach for combining these two different measurement technologies, leading to a robust position estimation in the presence of DM. We assume that a large ensemble of densely-spaced devices is to be positioned. We use RSS measurements to determine "clusters" of devices in the vicinity of each other. Joint processing of the WB measurements from all devices in a cluster efficiently suppresses the influence of the DM. We formulate an algorithmic approach for the information fusion of the two technologies and derive the corresponding Cramér-Rao lower bound (CRLB) to gain insight into the performance trade-offs at hand. We evaluate our results by simulations and validate the approach with real-world measurement data. The results show that the clustering approach can halve the root-mean-square error (RMSE) from about 2 m to below 1 m, using WB signal transmissions in the 2.4 GHz ISM band at a bandwidth of about 80 MHz.

Low-Complexity Joint Angle of Arrival and Time of Arrival Estimation of Multipath Signal in UWB System.

In an ultra-wideband (UWB) system, the two-dimensional (2D) multiple signal classification (MUSIC) algorithms based on high-precision 2D spectral peak search can jointly estimate the time of arrival (TOA) and angle of arrival (AOA). However, the computational complexity of 2D-MUSIC is very high, and the corresponding data model is only based on the dual antennas. To solve these problems, a low-complexity algorithm for joint AOA and TOA estimation of the multipath ultra-wideband signal is proposed. Firstly, the dual antenna sensing data model is extended to the antenna array case. Then, based on the array-sensing data model, the proposed algorithm transforms the 2D spectral peak search of 2D-MUSIC into a secondary optimization problem to extract the estimation of AOA via only 1D search. Finally, the acquired AOA estimations are brought back, and the TOA estimations are also obtained through a 1D search. Moreover, in the case of an unknown transmitted signal waveform, the proposed method can still distinguish the main path signal based on the time difference of arrival of different paths, which shows wider applications. The simulation results show that the proposed algorithm outperforms the Root-MUSIC algorithm and the estimation of signal parameters using the rotational invariance techniques (ESPRIT) algorithm, and keeps the same estimation accuracy but with greatly reduced computational complexity compared to the 2D-MUSIC algorithm.

A Suboptimal Optimizing Strategy for Velocity Vector Estimation in Single-Observer Passive Localization.

In a single-observer passive localization system, the velocity and position of the target are estimated simultaneously. However, this can lead to correlated errors and distortion of the estimated value, making independent estimation of the speed and position necessary. In this study, we introduce a novel optimization strategy, suboptimal estimation, for independently estimating the velocity vector in single-observer passive localization. The suboptimal estimation strategy converts the estimation of the velocity vector into a search for the global optimal solution by dynamically weighting multiple optimization criteria from the starting point in the solution space. Simulation verification is conducted using uniform motion and constant acceleration models. The results demonstrate that the proposed method converges faster with higher accuracy and strong robustness.

Ovarian Clear Cell Carcinoma and Rectal Adenocarcinoma Detected by Tubo-Ovarian Abscess: A Case Report.

Most cases of tubo-ovarian abscess (TOA) are due to transvaginal infection, while other internal diseases may also be associated with TOAs. We experienced a case of ovarian clear cell carcinoma and rectal carcinoma that was discovered to be a result of TOA. A 46-year-old woman was diagnosed with TOA and referred to our hospital. Laparoscopic abscess drainage was performed, and pathological findings confirmed the presence of ovarian clear cell carcinoma inside the abscess. The tumor marker carcinoembryonic antigen (CEA) was elevated, and rectal cancer was diagnosed by a gastrointestinal endoscopy. Abdominal computed tomography (CT) showed a left adnexal abscess with an air image inside, and penetration of the abscess wall and rectal cancer were observed. Histopathologically, there was an accumulation of neutrophils around the rectal tumor cells. We concluded that the rectal cancer had penetrated the existing ovarian tumor and formed TOA. Non-gynecological diseases may be associated with TOA. It is necessary to consider the possibility that other clinical diseases may be associated with the trigger of TOA.

Fixed Point Iteration Based Algorithm for Asynchronous TOA-Based Source Localization.

This paper investigates the problem of source localization using signal time-of-arrival (TOA) measurements in the presence of unknown start transmission time. Most state-of-art methods are based on convex relaxation technologies, which possess global solution for the relaxed optimization problem. However, computational complexity of the convex optimization-based algorithm is usually large, and need CVX toolbox to solve it. Although the two stage weighted least squares (2SWLS) algorithm has very low computational complexity, its estimate performance is susceptible to sensor geometry and threshold phenomenon. A new algorithm that is directly derived from maximum likelihood estimator (MLE) is developed. The newly proposed algorithm is named as fixed point iteration (FPI); it only involves simple calculations, such as addition, multiplication, division, and square-root. Unlike state-of-the-art methods, there is no matrix inversion operation and can avoid the unstable performance incurred by singular matrix. The FPI algorithm can be easily extended to the scenario with sensor position errors. Finally, simulation results demonstrate that the proposed algorithm reaches a good balance between computational complexity and localization accuracy.

Mobile Location in Wireless Sensor Networks Based on Multi Spot Measurements Model.

The localization of sensors in wireless sensor networks has recently gained considerable attention. The existing location methods are based on a one-spot measurement model. It is difficult to further improve the positioning accuracy of existing location methods based on single-spot measurements. This paper proposes two location methods based on multi-spot measurements to reduce location errors. Because the multi-spot measurements model has more measurement equations than the single-spot measurements model, the proposed methods provide better performance than the traditional location methods using one-spot measurement in terms of the root mean square error (RMSE) and Cramer-Rao lower bound (CRLB). Both closed-form and iterative algorithms are proposed in this paper. The former performs suboptimally with less computational burden, whereas the latter has the highest positioning accuracy in attaining the CRLB. Moreover, a novel CRLB for the proposed multi-spot measurements model is also derived in this paper. A theoretical proof shows that the traditional CRLB in the case of single-spot measurements performs worse than the proposed CRLB in the case of multi-spot measurements. The simulation results show that the proposed methods have a lower RMSE than the traditional location methods.

On-Orbit Absolute Radiometric Calibration and Validation of ZY3-02 Satellite Multispectral Sensor.

This study described the on-orbit vicarious radiometric calibration of Chinese civilian high-resolution stereo mapping satellite ZY3-02 multispectral imager (MUX). The calibration was based on gray-scale permanent artificial targets, and multiple radiometric calibration tarpaulins (tarps) using a reflectance-based approach between July and September 2016 at Baotou calibration site in China was described. The calibration results reveal a good linear relationship between DN and TOA radiances of ZY3-02 MUX. The uncertainty of this radiometric calibration was 4.33%, indicating that radiometric coefficients of ZY3-02 MUX are reliable. A detailed discussion on the validation analysis of the comparison results between the different radiometric calibration coefficients is presented in this paper. To further validate the reliability of the three coefficients, the calibrated ZY3-02 MUX was compared with Landsat-8 Operational Land Imager (OLI). The results also indicate that radiometric characteristics of ZY3-02 MUX imagery are reliable and highly accurate for quantitative applications.

Novel Solutions to the Three-Anchor ToA-Based Three-Dimensional Positioning Problem.

At least four non-coplanar anchor nodes (ANs) are required for the time-of-arrival (ToA)-based three-dimensional (3D) positioning to enable unique position estimation. Direct method (DM) and particle filter (PF) algorithms were developed to address the three-anchor ToA-based 3D positioning problem. The proposed DM reduces this problem to the solution of a quadratic equation, exploiting the knowledge about the workspace, to first estimate the x- or z-coordinate, and then the remaining two coordinates. The implemented PF uses 1000 particles to represent the posterior probability density function (PDF) of the AN's 3D position. The prediction step generates new particles by a resampling procedure. The ToA measurements determine the importance of these particles to enable updating the posterior PDF and estimating the 3D position of the AN. Simulation results corroborate the viability of the developed DM and PF algorithms, in terms of accuracy and computational cost, in the pursuit and circumnavigation scenarios, and even with a horizontally coplanar arrangement of the three ANs. Therefore, it is possible to enable applications requiring real-time positioning, such as unmanned aerial vehicle (UAV) autonomous docking and circling a stationary (or moving) position, without the need for an excessive number of ANs.

The role of "penumbra sign" and diffusion-weighted imaging in adnexal masses: do they provide a clue in differentiating tubo-ovarian abscess from ovarian malignancy?

PURPOSE: To evaluate the role of "penumbra sign", diffusion-weighted imaging (DWI), and the apparent diffusion coefficient (ADC) value in differentiating tubo-ovarian abscess (TOA) from ovarian malignancy. MATERIAL AND METHODS: Thirty-six patients with 50 adnexal masses (tubo-ovarian abscess, n = 24; ovarian malignancy, n = 26), who underwent magnetic resonance imaging (MRI) with DWI, were retrospectively evaluated. "Penumbra sign" (hyperintense rim on T1W images), diffusion restriction, and mean apparent diffusion coefficient (ADC) values from cystic (c-ADC) and solid (s-ADC) components were evaluated for all the masses. RESULTS: "Penumbra sign" on T1W images was significantly more common in the TOA group (n = 21, 87.5%) than in the ovarian malignancy group (n = 2, 7.7%) (p < 0.001). Similarly, diffusion restriction in the cystic component was more frequent in the TOA group (n = 24, 100% vs. n = 2, 10.5%; p < 0.001). In contrast, diffusion restriction in the solid component was more common in the ovarian malignancy group (n = 5, 20.8% vs. n = 26, 100%; p < 0.001). The mean c-ADC value was significantly lower in TOAs (p < 0.001). A c-ADC value of 1.31 × 10-3 mm2/s may be an optimal cut-off in distinguishing TOAs from ovarian malignancies. Conversely, the mean s-ADC value was significantly lower in the ovarian malignancy group (p < 0.001). An s-ADC value of 0.869 × 10-3 mm2/s may be an optimal cut-off in differentiating ovarian malignancies from TOAs (p < 0.001). ROC curve analysis showed that c-ADC values had a higher diagnostic accuracy than s-ADC values. CONCLUSIONS: "Penumbra sign" on T1W images, diffusion characteristics, and ADC values provide important clues in addition to conventional MR imaging features in differentiating TOA from ovarian malignancy.

Mobile Synchronization Recovery for Ultrasonic Indoor Positioning.

The growing interest for indoor position-based applications and services, as well as ubiquitous computing and location aware information, have led to increasing efforts toward the development of positioning techniques. Many applications require accurate positioning or tracking of people and assets inside buildings, and some market sectors are waiting for such technologies for starting a fast growth. Ultrasonic systems have already been shown to possess the desired positioning accuracy and refresh rate. However, they still require accurate synchronization between ultrasound emitters and receivers to work properly. Usually, synchronization is carried out through radio frequency (RF) signals, adding system complexity and raising the cost. In this work, this limit is overcome by introducing a novel self-synchronizing indoor positioning technique. Ultrasonic signals travel from emitters placed at fixed reference positions to any number of mobile devices (MD). The travelled distance is computed from the time of flight (TOF), which requires in turn synchronism between emitter and receiver. It is shown that this synchronism can be indirectly estimated from the time difference of arrival (TDOA) of the ultrasonic signals. The obtained positioning information is private, in the sense that the positioning infrastructure is not aware of the number or identity of the MDs that use it. Computer simulations and experimental results obtained in a typical office room are provided.

Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form.

The subject of localization has received great deal attention in the past decades. Although it is perhaps a well-studied problem, there is still room for improvement. Traditional localization methods usually assume the number of sensors is sufficient for providing desired performance. However, this assumption is not always satisfied in practice. This paper studies the time of arrival (TOA)-based source positioning in the presence of sensor position errors. An error refined solution is developed for reducing the mean-squared-error (MSE) and bias in small sensor network (the number of sensors is fewer) when the noise or error level is relatively large. The MSE performance is analyzed theoretically and validated by simulations. Analytical and numerical results show the proposed method attains the Cramér-Rao lower bound (CRLB). It outperforms the existing closed-form methods with slightly raising computation complexity, especially in the larger noise/error case.

MS Location Estimation Based on the Artificial Bee Colony Algorithm.

With the mature technology of wireless communications, the function of estimating the mobile station (MS) position has become essential. Suppressing the bias resulting from non-line-of-sight (NLSO) scenarios is the main issue for a wireless location network. The artificial bee colony (ABC) algorithm, based on the depiction of bee swarm's foraging characteristics, is widely applied to solve optimization problems in several fields. Based on three measurements of time-of-arrival (TOA), an objective function is used to quantify the additional NLOS error on the MS positioning scheme. The ABC algorithm is adopted to locate the most precise MS location by minimizing the objective function value. The performance of the proposed positioning methods is verified under various error distributions through computer simulations. Meanwhile, the localization accuracy achieved by other existing methods is also investigated. According to the simulation results, accurate estimation of the MS position is derived and therefore the efficiency of the localization process is increased.

Estimating PM2.5 concentrations in Yangtze River Delta region of China using random forest model and the Top-of-Atmosphere reflectance.

Previous studies that have used remote sensing data to estimate the PM2.5 concentrations mainly focused on the retrieval of aerosol optical depth (AOD) with moderate-to-low spatial resolution. However, the complex process of retrieving AOD from satellite Top-of-Atmosphere (TOA) reflectance always generates the missingness of AOD values due to the limitation of AOD retrieval algorithms. This study validated the possibility of using satellite TOA reflectance for estimating PM2.5 concentrations, rather than using conventional AOD products retrieved from remote sensing imageries. Given that the TOA-PM2.5 relationship cannot be accurately expressed by simple linear correlation, we developed a random forest model that integrated satellite TOA reflectance from Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1B product, meteorological fields and land-use variables to estimate the ground-level PM2.5 concentrations. The highly-polluted Yangtze River Delta (YRD) region of eastern China was employed as our study case. The results showed that our model performed well with a site-based and a time-based CV R2 of 0.92 and 0.88, respectively. The derived annual and seasonal distributions of PM2.5 concentrations exhibited high PM2.5 values in northern YRD region (i.e., Jiangsu province) and relatively low values in southern region (i.e., Zhejiang province), which shared a similar distribution trend with the observed PM2.5 concentrations. This study demonstrated the outstanding performance of random forest model using satellite TOA reflectance, and also provided an effective method for remotely sensed PM2.5 estimation in regions where AOD retrievals are unavailable.

Surgical Intervention in Patients with Tubo-Ovarian Abscess: Clinical Predictors and a Simple Risk Score.

STUDY OBJECTIVE: To identify the clinical characteristics associated with surgical intervention in patients with tubo-ovarian abscess (TOA). DESIGN: Retrospective cohort study (Canadian Task Force classification II-2). SETTING: Tertiary university-affiliated hospital. PATIENTS: Three hundred thirty-five patients were diagnosed with TOA based on sonographic and clinical criteria. Patients who underwent surgical intervention were compared with patients managed conservatively. INTERVENTION: Electronic medical records were used to identify patients who were diagnosed with TOA between 2007 and 2015. All patients received the same antibiotic regimen upon admission. The data extracted included microbial and pathologic reports. Clinical characteristics such as disease severity and outcomes were compared. The clinical predictors available on patient admission for surgical intervention were identified retrospectively. A logistic regression was used to determine the independent predictors of treatment failure. A risk score was created by giving a nominal weight to each predictor. The score was validated by a random bootstrap analysis. An additional validation cohort that consisted of patients diagnosed with TOA during the 2 years after the original study period was applied to the final score. MEASUREMENTS AND MAIN RESULTS: The following variables of patients who underwent surgical intervention in comparison with those successfully treated and were enrolled into the score analysis differed significantly: age at admission (odds ratio [OR], 2.1; 95% confidence interval [CI], 1.3-3.5), mean leukocytosis at admission (OR, 2.2; 95% CI, 1.3-3.6), ultrasonographic measurement of abscess diameter (OR, 3.6 95% CI, 2.0-6.3), and the presence of bilateral abscess (OR, 2.2; 95% CI, 1.3-3.9). Risk groups A, B, C, and D were positively correlated with the need for surgical intervention. Those in the highest risk group D had an antibiotic failure rate of 92%, as compared with those with the lowest risk group, in which there was a 20% risk of antibiotic failure. CONCLUSIONS: Antibiotic treatment failure for TOA can be predicted on patient admission using a novel risk assessment score.

Decawave UWB Clock Drift Correction and Power Self-Calibration.

The position accuracy based on Decawave Ultra-Wideband (UWB) is affected mainly by three factors: hardware delays, clock drift, and signal power. This article discusses the last two factors. The general approach to clock drift correction uses the phase-locked loop (PLL) integrator, which we show is subject to signal power variations, and therefore, is less suitable for clock drift correction. The general approach to the estimation of signal power correction curves requires additional measurement equipment. This article presents a new method for obtaining the curve without additional hardware and clock drift correction without the PLL integrator. Both correction methods were fused together to improve two-way ranging (TWR).

Target Localization via Integrated and Segregated Ranging Based on RSS and TOA Measurements.

This work addresses the problem of target localization in adverse non-line-of-sight (NLOS) environments by using received signal strength (RSS) and time of arrival (TOA) measurements. It is inspired by a recently published work in which authors discuss about a critical distance below and above which employing combined RSS-TOA measurements is inferior to employing RSS-only and TOA-only measurements, respectively. Here, we revise state-of-the-art estimators for the considered target localization problem and study their performance against their counterparts that employ each individual measurement exclusively. It is shown that the hybrid approach is not the best one by default. Thus, we propose a simple heuristic approach to choose the best measurement for each link, and we show that it can enhance the performance of an estimator. The new approach implicitly relies on the concept of the critical distance, but does not assume certain link parameters as given. Our simulations corroborate with findings available in the literature for line-of-sight (LOS) to a certain extent, but they indicate that more work is required for NLOS environments. Moreover, they show that the heuristic approach works well, matching or even improving the performance of the best fixed choice in all considered scenarios.