Cumulative Distribution Function Research Articles

High-risk powered two-wheelers scenarios generation for autonomous vehicle testing using WGAN

Objective Autonomous vehicles (AVs) have the potential to revolutionize the future of mobility by significantly improving traffic safety. This study presents a novel method for validating the safety performance of AVs in high-risk scenarios involving powered 2-wheelers (PTWs). By generating high-risk scenarios using in-depth crash data, this study is devoted to addressing the challenge of public road scenarios in testing, which often lack the necessary complexity and risk to effectively evaluate the capabilities of AVs in high-risk situations. Method Our approach employs a Wasserstein generative adversarial network (WGAN) to generate high-risk scenes, particularly focusing on PTW scenarios. By extracting 314 car-to-PTW crashes from the China In-depth Mobility Safety Study–Traffic Accident database, we simulate outcomes using PC-Crash software. The data are divided into scenes at 0.1-s intervals, with WGAN generating numerous high-risk scenes. By using a cumulative distribution function (CDF), we sampled and analyzed the vehicle’s dynamic information to generate complete scenarios applicable to the test. The validation process involves using the SVL Simulator and the Baidu Apollo joint simulation platform to evaluate the AV’s driving behavior and interactions with PTWs. Results This study evaluates model generation results by comparing distributions using Wasserstein distance as an indicator. The generator converges after approximately 200 epochs, with the iterator converging quickly. Subsequently, 10,000 new scenes are then generated. The distribution of several key parameters in the generated scenes can be found to approximate that of the original scenes. After sampling, the usability of generated scenarios is 64.76%. Virtual simulations confirm the effectiveness of the scenario generation method, with a generated scenario crash rate of 16.50% closely reflecting the original rate of 15.0%, showcasing the method’s capacity to produce realistic and hazardous scenarios. Conclusions The experimental results suggest that these scenarios exhibit a level of risk similar to the original crashes and are effective for testing AVs. Consequently, the generated scenarios enhance the diversity of the scenario library and accelerate the overall testing process of AVs.

Incidence of anaemia and its predictors among HIV-infected children receiving highly active antiretroviral treatment in North-West Ethiopia: a multicentre retrospective follow-up study

BackgroundAnaemia is one of the most common problems in HIV-infected patients associated with increased HIV progression, decreased functional capacity, survival and quality of life. For better interventions, up-to-date information concerning...

Current interventional model for movement in Parkinson's disease: network meta-analysis based on the improvement of motor ability.

To identify optimally therapeutic exercise interventions for improving motor ability among patients with Parkinson's disease (PD), we conducted a network meta-analysis (NMA) of randomized controlled trials comparing different exercise regimens. Relevant RCTs were retrieved by searching PubMed, Embase, Cochrane, Web of Science, CINAHL, CBM, China National Knowledge Infrastructure (CNKI), Wan fang, VIP, and other databases from inception to July 9, 2023 is available in English as the primary language. Exercise outcomes as measured by Movement Disorder Society- Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS-III) score change were evaluated and ranked using STATA software version 18.0. All included studies were assessed for methodological quality using the Cochrane Risk of Bias tool. The final NMA included 71 studies involving 3,732 participants, 87 intervention experiments, and 27distinct interventions. Although most exercise interventions showed some efficacy (reducing MDS-UPDRS-III score), cumulative ranking probability surface (SUCRA) values indicated that the best exercise interventions for motor function improvement were archery (95.6%), riding a bicycle (80.9%), and binary rhythm dance (80.8%). An exercise intervention comprising archery, cycling, and(or) binary rhythm dance may yield superior improvements in motor function among patients with Parkinson's disease.

Association between surgeon training grade and the risk of revision following unicompartmental knee replacement: An analysis of National Joint Registry data.

Unicompartmental knee replacements (UKRs) are performed by surgeons at various stages in training with varying levels of supervision, but we do not know if this is a safe practice with comparable outcomes to consultant-performed UKR. The aim of this study was to use registry data for England and Wales to investigate the association between surgeon grade (consultant, or trainee), the senior supervision of trainees (supervised by a scrubbed consultant, or not), and the risk of revision surgery following UKR. We conducted an observational study using prospectively collected data from the National Joint Registry for England and Wales (NJR). We included adult patients who underwent primary UKR for osteoarthritis (n = 106,206), recorded in the NJR between 2003 and 2019. Exposures were the grade of the operating surgeon (consultant, or trainee) and whether or not trainees were directly supervised by a consultant during the procedure (referred to as "supervised by a scrubbed consultant"). The primary outcome was all-cause revision surgery. The secondary outcome was the number of procedures revised for the following specific indications: aseptic loosening/lysis, infection, progression of osteoarthritis, unexplained pain, and instability. Flexible parametric survival models were adjusted for patient, operation, and healthcare setting factors. We included 106,206 UKRs in 91,626 patients, of which 4,382 (4.1%) procedures were performed by a trainee. The unadjusted cumulative probability of failure at 15 years was 17.13% (95% CI [16.44, 17.85]) for consultants, 16.42% (95% CI [14.09, 19.08]) for trainees overall, 15.98% (95% CI [13.36, 19.07]) for trainees supervised by a scrubbed consultant, and 17.32% (95% CI [13.24, 22.50]) for trainees not supervised by a scrubbed consultant. There was no association between surgeon grade and all-cause revision in either crude or adjusted models (adjusted HR = 1.01, 95% CI [0.90, 1.13]; p = 0.88). Trainees achieved comparable all-cause survival to consultants, regardless of the level of scrubbed consultant supervision (supervised: adjusted HR = 0.99, 95% CI [0.87, 1.14]; p = 0.94; unsupervised: adjusted HR = 1.03, 95% CI [0.87, 1.22]; p = 0.74). Limitations of this study relate to its observational design and include: the potential for nonrandom allocation of cases by consultants to trainees; residual confounding; and the use of the binary variable "surgeon grade," which does not capture variations in the level of experience between trainees. This nationwide study of UKRs with over 16 years' follow up demonstrates that trainees within the current training system in England and Wales achieve comparable all-cause implant survival to consultants. These findings support the current methods by which surgeons in England and Wales are trained to perform UKR.

Methodology for Generating a Reference Wind Year for Offshore Wind Energy: A Case Study in La Guajira, Colombia

Due to its excellent potential, wind power has gained importance as a renewable energy source in Colombia, especially in the offshore Caribbean region. However, one of the main challenges in the development of offshore wind projects is the analysis of the wind resource. This study presents the generation of a specific typical meteorological year (TMY) for wind energy in the Colombian Caribbean region, known in the literature as Reference Wind Year (RWY). The methodology used was based on the Sandia method, widely accepted in the analysis of wind resources. A comparison between the cumulative distribution function (CDF) and the statistic approach Finkelstein-Schafer (FS) was applied to evaluate multiple meteorological parameters in the study area associated with wind resource potential assessment, such as wind speed and direction, temperature and atmospheric pressure, compiled for 10 years (2012-2021). The representative years were weighted according to their importance and combined into a dataset. The results indicated that the proposed method was able to generate highly representative and accurate data for the case study in La Guajira, Colombia, guaranteeing its suitability for implementation in other locations with different climatic conditions.

Data-Aided Maximum Likelihood Joint Angle and Delay Estimator Over Orthogonal Frequency Division Multiplex Single-Input Multiple-Output Channels Based on New Gray Wolf Optimization Embedding Importance Sampling.

In this paper, we propose a new data-aided (DA) joint angle and delay (JADE) maximum likelihood (ML) estimator. The latter consists of a substantially modified and, hence, significantly improved gray wolf optimization (GWO) technique by fully integrating and embedding within it the powerful importance sampling (IS) concept. This new approach, referred to hereafter as GWOEIS (for "GWO embedding IS"), guarantees global optimality, and offers higher resolution capabilities over orthogonal frequency division multiplex (OFDM) (i.e., multi-carrier and multi-path) single-input multiple-output (SIMO) channels. The traditional GWO randomly initializes the wolfs' positions (angles and delays) and, hence, requires larger packs and longer hunting (iterations) to catch the prey, i.e., find the correct angles of arrival (AoAs) and time delays (TDs), thereby affecting its search efficiency, whereas GWOEIS ensures faster convergence by providing reliable initial estimates based on a simplified importance function. More importantly, and beyond simple initialization of GWO with IS (coined as IS-GWO hereafter), we modify and dynamically update the conventional simple expression for the convergence factor of the GWO algorithm that entirely drives its hunting and tracking mechanisms by accounting for new cumulative distribution functions (CDFs) derived from the IS technique. Simulations unequivocally confirm these significant benefits in terms of increased accuracy and speed Moreover, GWOEIS reaches the Cramér-Rao lower bound (CRLB), even at low SNR levels.

Extropy and entropy estimation based on progressive Type-I interval censoring

This paper proposes nonparametric estimates for the two information measures extropy and entropy when a progressively Type-I interval censored data is available. Different nonparametric approaches are used for deriving the estimates, including: moments of the empirical cumulative distribution function and linear regression. The performance of the proposed estimates is studied under various censoring schemes via simulation studies. Furthermore, different real data sets are analyzed for illustrative purposes.The estimates based on linear approximation J^2 and H^2 outperform the other estimate in the majority of studied cases.

Modified ex-PRESS technique versus Ahmed glaucoma valve as primary glaucoma surgery for hereditary transthyretin amyloidosis glaucoma

Background To compare the efficacy of modified Ex-PRESS technique (ExP) versus Ahmed Glaucoma Valve (AGV) as primary surgery in hereditary transthyretin amyloidosis (ATTRv) secondary glaucoma. Methods Retrospective study at the national amyloidosis centre. Success was defined as an IOP ≥ 6 mmHg and ≤ 21 mmHg with no need for further glaucoma surgery or laser trabeculoplasty and without loss of light perception at the time of the last follow-up. Secondary outcomes included surgical complications, need for hypotensive drugs, and endothelial cell loss. Patients submitted to previous glaucoma surgery were excluded. Results We included 180 eyes of 150 patients, 121 in AGV and 59 in ExP group. No significant baseline differences were found between groups. At the time of last follow-up, both groups exhibited significant intraocular pressure (IOP) reduction (p < .001) and number of glaucoma medications (p < .001). Kaplan-Meyer analysis showed higher cumulative probability of success for AGV group (80.1% vs. 41.1%, p < .001) and higher mean time to failure (54.5 vs. 36.9 months, respectively, p < 0.001) at 60 months follow-up. AGV showed lower hazard (HR 0.21, 95% CI [0.111–0.407], p < .001) for failure. Conclusion AGV and ExP are safe and effective techniques in the treatment of ATTRv secondary glaucoma. However, AGV’s efficacy seems to be more durable.

Capacity Optimization for RSMA-Based Multi-User System over Underwater Turbulence Channel

The underwater environment used for communication is harsh and complex, necessitating heightened standards for spectral efficiency and reliability in underwater wireless optical communication (UWOC) systems. The focus of this work is on the performance of multi-user UWOC systems operating in oblique channels of ocean turbulence downlink, where users are randomly distributed at a certain depth. A joint optimization scheme is proposed, which joints rate-splitting multiple access (RSMA) and power allocation so that the system’s ergodic sum capacity is optimized to improve the transmission bandwidth. Furthermore, the probability density function (PDF) and cumulative distribution function (CDF) models for the received signal-to-noise ratio (SNR) of a multi-user multiple-input multiple-output (MIMO) system operating in the turbulent underwater oblique channels are established, accounting for the avalanche photodiode (APD) shot noise and solar radiation noise. Theoretical derivations are presented to quantify the ergodic capacity and outage probability of the multi-user system utilizing the RSMA technology. Subsequently, a numerical analysis is conducted to investigate the influence of the power allocation coefficient, RSMA, and the joint optimization algorithm on the performance of a two-user MIMO system leveraging RSMA. The simulation results show that our optimization scheme effectively reduces the outage probability, thereby achieving the maximum system sum rate and validating the practical feasibility and efficacy of the proposed scheme.

Recurrence following successful eradication of neoplasia with endoscopic mucosal resection compared with endoscopic submucosal dissection in Barrett's esophagus: a retrospective comparison.

Endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD) are effective treatments for Barrett's neoplasia. However, little is known about recurrence rates following these techniques. We compared long-term neoplasia recurrence rates following EMR and ESD. This study included patients with Barrett's neoplasia (high grade dysplasia/adenocarcinoma) treated between July 2019 and December 2023 at a tertiary referral center in Canada. Outcomes were residual neoplasia at first follow-up, complete remission of neoplasia (CRN), and neoplasia recurrence following CRN. 157 patients were included (87 EMR, 70 ESD). Compared with EMR, the ESD group had larger lesions (median 2 vs. 3 cm, P<0.05), more adenocarcinoma (85.1% vs. 94.3%, P = 0.07), and deeper submucosal invasion (T1a: 71.6% vs. 75.8%; T1b-SM1: 25.7% vs. 6.1%; T1b≥SM2: 2.7% vs. 18.2%; P<0.05). Among 124 patients with follow-up (71 EMR, 53 ESD), 84.9% of ESD-treated patients had curative resections (i.e. R0 resection with low risk for lymph node metastasis), whereas 94.4% of EMR-treated patients had deep margin R0 resection of low risk lesions. At first follow-up, residual neoplasia (14.1% vs. 11.3%) and CRN (97.2% vs. 100%) were similar in the EMR and ESD groups, but neoplasia recurrence following CRN was significantly higher with EMR (13% vs. 1.9%, P<0.05), with cumulative probability of recurrence at 3 years of 18.3% vs. 4.2%, respectively. Neoplasia recurrence following CRN was significantly higher following EMR compared with ESD, suggesting that ESD may be superior to EMR in preventing neoplasia recurrence in Barrett's esophagus.

Performance Evaluation of CF-MMIMO Wireless Systems Using Dynamic Mode Decomposition

Cell-Free Massive Multiple-Input–Multiple-Output (CF-MIMO) systems have transformed the landscape of wireless communication, offering unparalleled enhancements in Spectral Efficiency and interference mitigation. Nevertheless, the large-scale deployment of CF-MIMO presents significant challenges in processing signals in a scalable manner. This study introduces an innovative methodology that leverages the capabilities of Dynamic Mode Decomposition (DMD) to tackle the complexities of Channel Estimation in CF-MIMO wireless systems. By extracting dynamic modes from a vast array of received signal snapshots, DMD reveals the evolving characteristics of the wireless channel across both time and space, thereby promising substantial improvements in the accuracy and adaptability of channel state information (CSI). The efficacy of the proposed methodology is demonstrated through comprehensive simulations, which emphasize its superior performance in highly mobile environments. For performance evaluation, the most common techniques have been employed, comparing the proposed algorithms with traditional methods such as MMSE (Minimum Mean Squared Error), MRC (Maximum Ration Combining), and ZF (Zero Forcing). The evaluation metrics used are standard in the field, namely the Cumulative Distribution Function (CDF) and the average UL/DL Spectral Efficiency. Furthermore, the study investigates the impact of DMD-enabled Channel Estimation on system performance, including beamforming strategies, spatial multiplexing within realistic time- and delay-correlated channels, and overall system capacity. This work underscores the transformative potential of incorporating DMD into massive MIMO wireless systems, advancing communication reliability and capacity in increasingly dynamic and dense wireless environments.

Indoor fingerprint localization algorithm based on WKNN and LightGBM-GA

Abstract WiFi-based indoor fingerprint localization is widely used in indoor localization owing to its high accuracy and low deployment costs. Changes in the indoor signal environment directly affect localization accuracy. To improve localization accuracy and stability, this paper proposes a novel indoor fingerprint localization algorithm based on Weighted K-Nearest Neighbors (WKNN) and an enhanced Light Gradient Boosting Machine (LightGBM). First, in the offline phase, Gaussian filtering and K-Nearest Neighbors-Random Forest information completion algorithm with fusion of Euclidean and Manhattan distances are used to remove outliers from the fingerprint database dataset and fill in missing fingerprint information, ensuring the integrity of the fingerprint database. During the online phase, the fingerprint database is divided into training and testing sets. The LightGBM algorithm is used for modeling. Additionally, Genetic Algorithm (GA) is use d to optimize the parameters of LightGBM algorithm to find the best parameters by fitness evaluation. Then, the nearest neighbor set found by the WKNN algorithm is introduced into the LightGBM-GA model. Combining the predictions from the standalone LightGBM algorithm and performing weighted fusion yields the final predicted coordinates. The experiments are conducted in 8 m × 10 m laboratory containing 5 access points and 80 reference points to collect the Received Signal Strength Indication values of 5 WiFi hotspots. The experimental results show that the average localization error of the proposed algorithm is 1.11 m, which is reduced by 6.7%–38.3% compared to K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), LightGBM, KNN + XGBoost, WKNN + LightGBM, and WKNN + XGBoost-GA localization algorithms. The localization curve is smoother, and the cumulative distribution function converges faster. Moreover, the localization time is reduced by 13.3%–36.7%, effectively enhancing localization accuracy and decreasing localization time.

Individual Identification and Assessment of Genetic Diversity Using Microsatellite Markers in Racing Pigeons Raised in Turkiye

The implementation of a swift and economical molecular genetic approach, ensuring both efficacy and cost-effectiveness and facilitating population certification, is of utmost significance for breeders and the conservation of Turkiye's native pigeon biodiversity. In this study, we aimed to examine the genetic structure of racing pigeons (Columba livia domestica) raised in Turkiye using a genetic marker panel consisting of eight short tandem repeat (STR) loci. For this purpose, DNA was isolated from the shed feathers of 216 pigeons. Genomic DNA was amplified using the multiplex allele-specific PCR and subsequent capillary electrophoresis with ABI PRISM 3130XL Genetic Analyzer. Next, PCR products were analyzed in the GeneMapper Software program (Applied Biosystems). For parent testing, paternity index (PI), combined paternity index (CPI), and cumulative probability of paternity (CPP) were calculated. Furthermore, population genetic diversity was evaluated using heterozygosity (He), polymorphism information content (PIC), and Hardy–Weinberg equilibrium (HWE) testing. Results revealed that the total number of alleles is 81 and the number of alleles per locus varies between 4 and 19. The similarity rate between parent and offspring was calculated as 99.99% and above. Since no pedigree information was given when the samples were analyzed, obtaining this similarity ratio demonstrates the reliability of the panel. He values range from 0.362 to 0.919, and the PIC values range from 0.295 to 0.909. Loci PG-1, PG-2, and PG-3 show significant genetic diversity, with moderate to high PIC values reflecting varied allele frequencies in the population. Consequently, the set of seven STR markers (+ one sex marker) can be applied to identify and confirm parentage on a regular basis, thereby facilitating efficient breeding programs and ensuring genetic diversity conservation. This panel enables efficient pedigree analysis and gender determination, optimizing cost-effectiveness. The methodology presented in this study is ideal for pedigree analysis and breed certification in the Turkish pigeon breeding industry. Consequently, we affirm that the study data carries considerable national importance.

Clinical features and surgical strategy of retroperitoneal liposarcoma involving the kidney capsule: a retrospective comparative cohort study.

Valid and generalizable data on the clinical features and surgical strategies for retroperitoneal liposarcoma (LPS) involving the kidney capsule remain scarce. This study aimed to investigate the clinical characteristics, morbidity, mortality, and long-term survival of patients with retroperitoneal LPS involving the kidney capsule. The authors analyzed a prospectively maintained database of patients who underwent surgical resection for retroperitoneal LPS between 2015 and 2020. The patients were categorized into kidney capsule or no kidney capsule groups based on the presence or absence of kidney capsule involvement. A kidney-sparing strategy for retroperitoneal LPS involving the kidney capsule was developed. The primary outcome measure was overall survival (OS). The cumulative event probability curve was estimated using the Kaplan-Meier, and differences between groups using the Log-Rank. The study population consisted of 128 patients-54 with and 74 without kidney capsule involvement. Of these patients, 70 were female (54.7%) and 58 were male (45.3%), with a median age of 55. The median follow-up duration was 35 months. Postoperative morbidity, mortality, length of hospital stay, length of ICU stay, OS, and recurrence-free survival (RFS) did not differ significantly between the groups. Eleven patients developed postoperative acute kidney injury (AKI), and one patient required dialysis during the follow-up period. In multivariable logistic regression analysis, only nephrectomy was independently associated with postoperative AKI. Subgroup analysis of patients with kidney capsule involvement showed that nephrectomy did not improve OS or RFS but significantly decreased postoperative estimated glomerular filtration rate. Nephrectomy was associated with an increased risk of postoperative AKI after retroperitoneal LPS resection. A kidney-sparing strategy for retroperitoneal LPS involving the kidney capsule achieved optimal clinical outcomes.

Stage-based recipient and donor outcome in twin-to-twin transfusion syndrome treated by fetoscopic laser surgery using Solomon technique.

To evaluate twin survival stratified by Quintero stage in patients with twin-to-twin transfusion syndrome (TTTS) after Solomon laser treatment. This was a single-center study at Johns Hopkins Center for Fetal Therapy, investigating a cohort of consecutive twin pregnancies treated with the Solomon laser technique for TTTS. Preoperative Quintero stage, perioperative characteristics and obstetric factors were investigated in relation to neonatal survival of the recipient and donor twins at discharge. Determinants of twin survival were evaluated using univariate logistic regression and cumulative survival probability analyses. Of 402 pregnancies with TTTS that underwent Solomon laser treatment, 80 (19.9%) were diagnosed with Quintero Stage-I TTTS, 126 (31.3%) with Stage II, 169 (42.0%) with Stage III and 27 (6.7%) with Stage IV. Post-laser twin anemia polycythemia sequence or recurrent TTTS occurred in 19 (4.7%) patients and 11 (2.7%) required repeat laser surgery. Preterm prelabor rupture of membranes occurred in 150 (37.3%) patients and median gestational age at delivery was 32 + 1 weeks. In 303 (75.4%) patients, both twins were alive at discharge; 67/80 (83.8%) were Stage I, 101/126 (80.2%) were Stage II, 113/169 (66.9%) were Stage III and 22/27 (81.5%) were Stage IV (P = 0.062). Donor twin survival was lower than that of recipients in cases with Stage-III TTTS (118/169 (69.8%) vs 145/169 (85.8%) (χ2 = 26.076, P < 0.0001)). Higher intertwin size discordance and absent or reversed umbilical artery (UA) end-diastolic velocity (EDV) were associated with donor demise (Nagelkerke R2, 0.38; P < 0.001). Overall, spontaneous post-laser donor demise occurred in 53 (39.6%) patients, accounting for the majority of all losses. Cumulative donor survival decreased from 92% to 65% when intertwin size discordance was >30% and to 48% when UA-EDV was absent or reversed (P < 0.001). The Solomon laser technique achieves TTTS resolution and double twin survival in a high proportion of cases. Recipient and donor survival is comparable unless there is significant intertwin size discordance and placental dysfunction. This degree of unequal placental sharing, typically found in Stage-III TTTS, is the primary factor preventing double survival due to a higher rate of donor demise. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Risk of cardiovascular events after influenza infection-related hospitalizations in adults with congenital heart disease: A nationwide population based study

BackgroundCardiovascular complications due to viral infection pose a significant risk in vulnerable patients such as those with congenital heart disease (CHD). Limited data exists regarding the incidence of influenza and its impact on cardiovascular outcomes among this specific patient population. MethodsA retrospective cohort study was designed using the Canadian Congenital Heart Disease (CanCHD) database - a pan-Canadian database of CHD patients with up to 35 years of follow-up. CHD patients aged 40 to 65 years with influenza virus-associated hospitalizations between 2010 and 2017 were identified and 1:1 matched with CHD patients with limb fracture hospitalizations on age and calendar time. Our primary endpoint was cardiovascular complications: heart failure, acute myocardial infarction, atrial arrhythmia, ventricular arrhythmia, heart block, myocarditis, and pericarditis. ResultsOf the 303 patients identified with incident influenza virus-associated hospitalizations, 255 were matched to 255 patients with limb fracture hospitalizations. Patients with influenza virus-related hospitalizations showed significantly higher cumulative probability of cardiovascular complications at one year (0.16 vs. 0.03) and five years (0.33 vs. 0.15) compared to patients hospitalized with bone fracture. Time-dependent hazard function modeling demonstrated a significantly higher risk of cardiovascular complications within nine months post-discharge for influenza-related hospitalizations. This association was confirmed by Cox regression model (average hazard ratio throughout follow-up: 2.48; 95% CI: 1.59 – 3.84). ConclusionsThis pan-Canadian cohort study of adults with CHD demonstrated an association between influenza virus-related hospitalization and risk of cardiovascular complications during the nine months post discharge. This data is essential in planning surveillance strategies to mitigate adverse outcomes and provides insights into interpreting complication rates of other emerging pathogens, such as COVID-19.

Atezolizumab Plus Bevacizumab Treatment for Unresectable Hepatocellular Carcinoma: Real-life Experience from a Single Tertiary Centre in Spain and ALBI Score as a Survival Prognostic Factor.

Atezolizumab/bevacizumab (atez/bev) has been established as first-line systemic treatment for hepatocellular carcinoma (HCC). However, concerns regarding safety and efficacy have been raised, and no biomarkers to predict response have yet been identified. We aimed to evaluate the real-life experience of atez/bev in a Spanish tertiary hospital and identify factors associated with overall survival (OS). A prospective study of consecutive patients with HCC treated with atez/bev was conducted from December 2020 to December 2022. Efficacy was assessed through OS and progression-free survival (PFS), whereas safety was evaluated based on adverse events (AE). Twenty-three patients were included; 91% were males with a mean of 70 years. Thirteen patients were classified as having BCLC-C. The median treatment duration was 126 days (range=567). Median OS was 381 days (95%CI=205-557) with a cumulative probability of death of 13%, 30%, and 49% at 3, 6 and 12-month follow-up, respectively. The only factor associated with OS was the ALBI score (HR=5.03; 95%CI=1.3-19.1), which showed an AUROC of 0.906 (95%CI=0.78-1.00) for the risk of death at 18 months follow up. Median PFS was 141 days (95%CI=110-172). Twenty (86.9%) patients experienced AE, which in nine (39.1%) cases led to the definitive discontinuation of the treatment, four of them (17.4%) due to an AE grade 5. The initial experience with atez/bev at our center demonstrated poorer outcomes compared to the original trial (IMbrave150). A careful assessment of the ALBI score may serve as a crucial factor in the selection of systemic treatment for patients with HCC.

The Optimal First-Line Therapy for Extensive-Stage Small-Cell Lung Cancer Based on Liver Metastasis Status: ANetwork Meta-Analysis and Systematic Review.

To compare the efficacy of first-line regimens based on programmed cell death (or ligand) [PD-(L)1] blockade in extensive-stage small-cell lung cancer (ES-SCLC) patients with or without liver metastases (LM), and to identify optimal treatment strategies. Network meta-analysis of randomized controlled trials (RCTs) comparing chemo-immunotherapy (CIT) and chemotherapy (CT) in ES-SCLC patients stratified by LM. Overall survival (OS) and progression-free survival (PFS) were evaluated using hazard ratios (HRs) and 95% confidence intervals (CIs). Seven RCTs involving 3658 ES-SCLC patients (1243 with LM, 2415 without LM) were analyzed. For patients with LM, the combination therapies of anti-PD-1 + CT (HR, 0.67; 95% CI, 0.54%-0.82%; p < 0.001) and anti-PD-L1 + CT + anti-angiogenesis (HR, 0.84; 95% CI, 0.71%-0.99%; p = 0.042) demonstrated superior efficacy in prolonging OS compared to CT alone. The anti-PD-1 + CT regimen had the highest cumulative probability of 91.6% for extending OS in patients with LM. For patients without LM, all CIT regimens resulted in improved OS compared to CT alone, with the regimen of anti-angiogenesis + anti-PD-L1 + CT ranking first and having the highest cumulative probability of 95.5% for prolonging OS. CIT is effective for ES-SCLC patients regardless of LM status. For patients with LM, PD-1 blockade combined with CT is the best option. For patients without LM, the most beneficial regimen is the combination of anti-angiogenesis, PD-L1 blockade, and CT.

Detection range of a passing submerged emitter of sound in ambient noisea).

An underwater acoustic detection problem is studied in which the ambient noise present at a receiver is calculated, given information describing environmental conditions, including windspeed, and the positions of nearby ships which act as sources of background noise. The signal, whose detection is sought, is narrowband and transmitted from a source that passes by the receiver along a straight track. Cumulative Probability of Detection (CPoD) is calculated along a series of tracks with increasing closest-point-of-approach distances to the receiver. Two detection ranges are analyzed, a so-called "defender" detection range and an "intruder" detection range. Both are conservative measures associated with CPoD equaling 0.5 during the transit of the submerged vessel. Predictions of the detection range are compared across independent attempts to solve the same problem with different modelling approaches. The spread of results (i.e., the "reproducibility" of the predictions) is discussed and reasons for differences are highlighted. Environmental conditions that strongly affect detection performance are discussed, as is the use of CPoD as a single-valued metric to describe detection performance.

Morph-SSL: Self-Supervision With Longitudinal Morphing for Forecasting AMD Progression From OCT Volumes.

The lack of reliable biomarkers makes predicting the conversion from intermediate to neovascular age-related macular degeneration (iAMD, nAMD) a challenging task. We develop a Deep Learning (DL) model to predict the future risk of conversion of an eye from iAMD to nAMD from its current OCT scan. Although eye clinics generate vast amounts of longitudinal OCT scans to monitor AMD progression, only a small subset can be manually labeled for supervised DL. To address this issue, we propose Morph-SSL, a novel Self-supervised Learning (SSL) method for longitudinal data. It uses pairs of unlabelled OCT scans from different visits and involves morphing the scan from the previous visit to the next. The Decoder predicts the transformation for morphing and ensures a smooth feature manifold that can generate intermediate scans between visits through linear interpolation. Next, the Morph-SSL trained features are input to a Classifier which is trained in a supervised manner to model the cumulative probability distribution of the time to conversion with a sigmoidal function. Morph-SSL was trained on unlabelled scans of 399 eyes (3570 visits). The Classifier was evaluated with a five-fold cross-validation on 2418 scans from 343 eyes with clinical labels of the conversion date. The Morph-SSL features achieved an AUC of 0.779 in predicting the conversion to nAMD within the next 6 months, outperforming the same network when trained end-to-end from scratch or pre-trained with popular SSL methods. Automated prediction of the future risk of nAMD onset can enable timely treatment and individualized AMD management.