Investigating Persistence in the US Mutual Fund Market: A Mobility Approach

Performance persistence in the US mutual fund market is investigated, modeling risk-adjusted performance as a Markov Chain. This allows us to explore whether there is a higher probability for funds to remain in their initial ranking, compared to the probability that funds exhibit some kind of movement. We find some degree of inertia due to non-uniformity of transition probabilities across states. Our analysis allows also assesses the proximity of empirical transition matrices to two benchmark matrices, identifying the no-persistence/perfect immobility cases. We find that the observed transition matrices are closer to the no-persistence benchmark and also that performance persistence has decreased over time

Secure and Agile 6G Networking:Quantum and AI Enabling Technologies

This paper proposes a novel architecture for enabling ultra-fast and ultra-safe 6G networks that can support complex and challenging real-time applications based on four key enabling technologies: 1) performance prediction, 2) AI-enabled task offloading, 3) quantum machine learning, and 4) quantum-resistant communication. With the emergence of 6G applications where the real-time quality of experience is prioritized, AI-enabled task offloading leverages the benefits of edge computing. Moreover, the execution time of complex applications can be reduced by using quantum computers at the edge or in the cloud. In addition, by incorporating quantum key distribution and post-quantum cryptography, we can ensure the safety of mobile networks in the quantum computing era. Collectively, these technologies will provide ultra-fast and ultra-safe 6G networks, meeting the requirements of challenging real-time applications that were not supported in the previous generations, thus advancing the state of the art of mobile communication networks

The Effect of Ball Heading and Subclinical Concussion On the Neuromuscular Control Of The Lower Limb: A Systematic Review

# Background Soccer is unique among sports because it is the only sport that involves purposeful use of the head to control, pass, or shoot the ball. Over the previous five years, a relationship between lower extremity (LE) injury and sports related concussion (SRC) has been established in various sporting populations. Athletes at the high school, collegiate, and professional levels have demonstrated a greater risk for sustaining a LE injury post SRC. The purpose of this systematic review was to examine the relationship of the SRC with the incidence of LE injuries. # Methods Ten databases were searched with the following keywords: Lower limb, ball heading, neuromuscular control, concussion, MEDLINE, Ovid MEDLINE(R) Daily, and Ovid MEDLINE(R), EMBASE, and Scopus. The search was limited to English-language and peer-reviewed publications, until 15/12/2022. The PEDro scale was used for the assessment of the risk of bias among the included studies. All included papers were qualitatively analyzed. # Results A total of 834 studies were identified and 10 articles (four concussion-MSK biomechanics, six concussion-MSK injury) were included in the qualitative analyses. Included papers ranged from low to high quality. Due to the heterogeneous nature of the included study designs, quantitative meta-analysis was unable to be performed. All four of the included concussion-MSK biomechanics studies demonstrated, to some degree, that worse cognitive performance was associated with lower extremity MSK biomechanical patterns suggestive of greater risk for MSK injury. Among the six injury related studies, two investigations failed to determine group differences in cognitive performance between subsequently injured and non-injured athletes. # Conclusion More research is needed to better understand the relationship of SRC and lower extremity injuries and the extent to which they are related to concussions and/or repetitive neurotrauma after ball heading sustained in soccer. # Level of Evidence

Preliminary diagnostic reference levels for endoscopic retrograde cholangio-pancreatography in Greece

The main objective of this study was to determine the preliminary Diagnostic Reference Levels (DRLs) in terms of Kerma Area Product (KAP) and fluoroscopy time (Tf) during Endoscopic Retrograde Cholangio-Pancreatography (ERCP) procedures. Additionally, an investigation was conducted to explore the statistical relation between KAP and Tf. Data from a set of 200 randomly selected patients treated in 4 large hospitals in Greece (50 patients per hospital) were analyzed in order to obtain preliminary DRLs for KAP and Tf during therapeutic ERCP procedures. Non-parametric statistic tests were performed in order to determine a statistically significant relation between KAP and Tf. The resulting third quartiles for KAP and Tf for hospitals (A, B, C and D) were found as followed: KAPA = 10.7 Gy cm^2, TfA = 4.9 min; KAPB = 7.5 Gy cm^2, TfB = 5.0 min; KAPC = 19.0 Gy cm^2, TfC = 7.3 min; KAPD = 52.4 Gy cm^2, TfD = 15.8 min. The third quartiles, calculated for the total 200 cases sample, are: KAP = 18.8 Gy cm^2 and Tf = 8.2 min. For 3 out of 4 hospitals and for the total sample, p-values of statistical indices (correlation of KAP and Tf) are less than 0.001, while for the Hospital A p-values are ranging from 0.07 to 0.08. Using curve fitting, we finally determine that the relation of Tf and KAP is deriving from a power equation (KAP = Tf^1.282) with R^2 = 0.85. The suggested Preliminary DRLs (deriving from the third quartiles of the total sample) for Greece are: KAP = 19 Gy cm^2 and Tf = 8 min, while the relation between KAP and Tf is efficiently described by a power equatio

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Deep Multimodal Emotion Recognition on Human Speech: A Review

This work reviews the state of the art in multimodal speech emotion recognition methodologies, focusing on audio, text and visual information. We provide a new, descriptive categorization of methods, based on the way they handle the inter-modality and intra-modality dynamics in the temporal dimension: (i) non-temporal architectures (NTA), which do not significantly model the temporal dimension in both unimodal and multimodal interaction; (ii) pseudo-temporal architectures (PTA), which also assume an oversimplification of the temporal dimension, although in one of the unimodal or multimodal interactions; and (iii) temporal architectures (TA), which try to capture both unimodal and cross-modal temporal dependencies. In addition, we review the basic feature representation methods for each modality, and we present aggregated evaluation results on the reported methodologies. Finally, we conclude this work with an in-depth analysis of the future challenges related to validation procedures, representation learning and method robustness

Inverse Design of ZIFs through Artificial Intelligence Methods

Artificial Intelligence (AI) benefits research on membrane separations by facilitating fast and accurate performance predictions of a given material. However, the potential of AI to work backwards, towards predicting/designing a finetuned material for a given separation, remains untapped. Recent works report the inverse design of functionalized materials, such as metal-organic frameworks (MOFs), but they are limited to targeted sorption properties, while diffusivity, D, which is the driving force in membrane-based separations, is omitted. Herein, we report a tool combining a biologically inspired evolutionary algorithm with machine learning to design fine-tuned Zeolitic-Imidazolate Frameworks (ZIFs), a sub-family of MOFs, for desired sets of diffusivities (Di, Di/Dj) values of any given mixture of species i and j. We moreover display the efficacy of our tool, by designing ZIFs that meet industrial performance criteria of permeability and selectivity, for CO2/CH4, O2/N2 and C3H6/C3H8 mixtures. We validate the designed ZIFs through appropriate simulations, confirming the suitability of the AI-suggested ZIF designs