Search Results (475)

A current challenge of irrigationengineering is to modernize surface irrigation. For example, surge flow irrigation has the potential to increase the efficiency of applying irrigationwater. The objective of this study was to perform a sensitivity analysis using the performance indices: Application Efficiency (AE), Storage Efficiency (SE), Distribution Efficiency (DE), Deep Percolation (DP), and Runoff (RO), and to investigate their relationship with the main system variables: length (L), unit flow rate (Q_o), surge cycles and surge time, using the SIRMOD model. The SIRMOD model simulates the hydraulics of surface irrigation at the field level. The model with the best fit of AE, DE, DP, and RO as a function of L, Q_o, or surge cycles and surge time was a quadratic polynomial function with an R² > 0.70. The model reflects the goodness of fit to the variable that is intended to be explained. The AE is an increasing function of L and a decreasing function of Q_o, while DE and RO are decreasing functions of L and are increasing functions of Q_o. The number of surges has an impact on the stream size of each surge and on the volume of water stored, but not on the performance indices. It was demonstrated that the SIRMOD model provided the ability to adjust the system parameters and design variables, giving answersto any surge flow configuration. The potential application efficiency (AE_pot) (>80%) can be achieved by establishing, e.g., an optimal flow rate (Q_opt), with a schedule for the cycle number and surge time, according to soil characteristics. Full article

The treatment of early triple-negative breast cancer (eTNBC) has improved patients’ prognosis but often leads to adverse events and sequelae affecting quality of life (QoL). Pain Neuroscience Education (PNE) is a promising non-pharmacological intervention in this field. Preliminary data have shown the beneficial effect of PNE in BC survivors. However, there are still gaps in knowledge regarding its optimal use in eTNBC. To address this issue, a prospective pilot study will enroll 30 consecutive patients diagnosed with eTNBC at IRCCS Humanitas Research Hospital. The PNE program will consist of 10 weekly sessions to be started within 4 weeks of the onset or worsening of a pain syndrome (PS). QoL, pain, and disability will be assessed before, during, at the end of, and 6 months after PNE using validated questionnaires. Peripheral venous blood samples will be taken before and at the end of PNE to evaluate inflammatory serum biomarker levels. The primary objective is to evaluate whether PNE leads to clinical improvement in QoL and pain. If successful, it will be validated in a larger multi-centric cohort, potentially leading to its widespread implementation as a standard pain management tool for eTNBC patients. Full article

Extended reality (XR) is an immersive technology widely applied in various fields. Due to the real-time interaction required between users and virtual environments, XR applications are highly sensitive to latency. Furthermore, handling computationally intensive tasks on wireless XR devices leads to energy consumption, which is a critical performance constraint for XR applications. It has been noted that the XR task can be decoupled to several subtasks with mixed serial–parallel relationships. Furthermore, the evaluation of XR application performance involves both subjective assessments from users and objective evaluations, such as of energy consumption. Therefore, in edge computing environments, ways to integrate task offloading for XR subtasks to meet users’ demands for XR applications is a complex and challenging issue. To address this issue, this paper constructs a wireless XR system based on mobile edge computing (MEC) and conducts research on the joint optimization of multi-user communication channel access and task offloading. Specifically, we consider the migration of partitioned XR tasks to MEC servers and formulate a joint optimization problem for communication channel access and task offloading. The objective is to maximize the ratio of quality of experience (QoE) to energy consumption while meeting the user QoE requirements. Subsequently, we introduce a deep reinforcement learning-based algorithm to address this optimization problem. The simulation results demonstrate the effectiveness of this algorithm in meeting user QoE demands and improving energy conversion efficiency, regardless of the XR task partitioning strategies employed. Full article

Network slicing is a concept introduced in 5G networks that supports the provisioning of multiple types of mobile services with diversified quality of service (QoS) requirements in a shared network. Network slicing concerns the placement/allocation of radio processing resources and traffic flow transport over the Xhaul transport network—connecting the 5G radio access network (RAN) elements—for multiple services while ensuring the slices’ isolation and fulfilling specific service requirements. This work focuses on modeling and optimizing network slicing in packet-switched Xhaul networks, a cost-effective, flexible, and scalable transport solution in 5G RANs. The considered network scenario assumes two types of network slices related to enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications (URLLC) services. We formulate a network slicing planning optimization problem and model it as a mixed-integer linear programming (MILP) problem. Moreover, we develop an efficient price-and-branch algorithm (PBA) based on column generation (CG). This advanced optimization technique allows for overcoming the MILP model’s poor performance when solving larger network problem instances. Using extensive numerical experiments, we show the advantages of the PBA regarding the quality of the solutions obtained and the computation times, and analyze the packet-switched Xhaul network’s performance in various network slicing scenarios. Full article

Deep Brain Stimulation (DBS) is a recognized treatment for different dystonia subtypes and has been approved by the Food and Drug Administration (FDA) since 2003. The European Federation of Neurological Societies (EFNS) and the International Parkinson and Movement Disorders Society (MDS) recommend DBS for dystonia after failure of botulinum toxin (BoNT) and other oral medications for dystonia treatment. In addition, several long-term studies have demonstrated the continuous efficacy of DBS on motor and quality of life (QoL) scores. However, there are only a few reports comparing the overall impact of surgical treatment in BoNT protocols (e.g., dosage and number of selected muscles before and after surgery). This retrospective multicenter chart-review study analyzed botulinum toxin total dosage and dosage per muscle in 23 dystonic patients before and after DBS surgery. The study’s primary outcome was to analyze whether there was a reduction in BoNT dosage after DBS surgery. The mean BoNT dosages difference between baseline and post-surgery was 293.4 units for 6 months, 292.6 units for 12 months, and 295.2 units at the last visit. The median total dose of BoNT in the preoperative period was 800 units (N = 23). At the last visit, the median was 700 units (p = 0.05). This represents a 12.5% reduction in BoNT median dosage. In conclusion, despite the limitations of this retrospective study, there was a significant reduction in BoNT doses after DBS surgery in patients with generalized dystonia. Full article

Background: Social rhythm dysregulation has been identified as a determining factor in bipolar disorder (BD) relapses. It directly impacts individuals’ quality of life (QoL). This study aims to present preliminary data on the efficacy of an e-health psychoeducational intervention for BD for improving clinical outcomes. Methods: This study used an open-label, crossover, randomized controlled trial design. The inclusion criteria consisted of a BD diagnosis, affiliation with the Consultation Psychiatry and Psychosomatic Center at the University Hospital in Cagliari, Italy, age over 18, and the obtaining of informed consent. Anxiety and depressive symptoms, QoL, and social and biological rhythms were measured using standardized instruments validated in Italian. Results: A total of 36 individuals were included in the experimental group (EG) and 18 in the control group (CG). The final sample consisted of 25 in the EG and 14 in the CG. A statistically significant improvement in QoL was found in the EG post-treatment (p = 0.011). Significant correlations were found between QoL and the dysregulation of biorhythms in the EG at T0 (p = 0.0048) and T1 (p = 0.0014). Conclusions: This study shows that, during extreme distress, an e-health group psychoeducation intervention for people with BD could significantly improve the perception of QoL. The results must be confirmed by studies conducted with larger-sized samples. Full article

With the boom in mobile internet services, computationally intensive applications such as virtual and augmented reality have emerged. Mobile edge computing (MEC) technology allows mobile devices to offload heavy computational tasks to edge servers, which are located at the edge of the network. This technique is considered an effective approach to help reduce the burden on devices and enable efficient task offloading. This paper addresses a dynamic real-time task-offloading problem within a stochastic multi-user MEC network, focusing on the long-term stability of system energy consumption and energy budget constraints. To solve this problem, a task-offloading strategy with long-term constraints is proposed, optimized through the construction of multiple queues to maintain users’ long-term quality of experience (QoE). The problem is decoupled using Lyapunov theory into a single time-slot problem, modeled as a Markov decision process (MDP). A deep reinforcement learning (DRL)-based LMADDPG algorithm is introduced to solve the task-offloading decision. Finally, Experiments are conducted under the constraints of a limited MEC energy budget and the need to maintain the long-term energy stability of the system. The results from simulation experiments demonstrate that the algorithm outperforms other baseline algorithms in terms of task-offloading decisions. Full article

Background: Endometriosis is a multifaceted gynecological condition that poses diagnostic challenges and affects a significant number of women worldwide, leading to pain, infertility, and a reduction in patient quality of life (QoL). Traditional diagnostic methods, such as the revised American Society for Reproductive Medicine (r-ASRM) classification, have limitations, particularly in preoperative settings. The Numerical Multi-Scoring System of Endometriosis (NMS-E) has been proposed to address these shortcomings by providing a comprehensive preoperative diagnostic tool that integrates findings from pelvic examinations and transvaginal ultrasonography. Methods: This retrospective study aims to validate the effectiveness of the NMS-E in predicting surgical outcomes and correlating with the severity of endometriosis. Data from 111 patients at Nippon Medical School Hospital were analyzed to determine the correlation between NMS-E scores, including E-score—a severity indicator—traditional scoring systems, surgical duration, blood loss, and clinical symptoms. This study also examined the need to refine parameters for deep endometriosis within the NMS-E to enhance its predictive accuracy for disease severity. Results: The mean age of the patient cohort was 35.1 years, with the majority experiencing symptoms such as dysmenorrhea, dyspareunia, and chronic pelvic pain. A statistically significant positive correlation was observed between the NMS-E’s E-score and the severity of endometriosis, particularly in predicting surgical duration (Spearman correlation coefficient: 0.724, p < 0.01) and blood loss (coefficient: 0.400, p < 0.01). The NMS-E E-score also correlated strongly with the r-ASRM scores (coefficient: 0.758, p < 0.01), exhibiting a slightly more excellent predictive value for surgical duration than the r-ASRM scores alone. Refinements in the methodology for scoring endometriotic nodules in uterine conditions improved the predictive accuracy for surgical duration (coefficient: 0.752, p < 0.01). Conclusions: Our findings suggest that the NMS-E represents a valuable preoperative diagnostic tool for endometriosis, effectively correlating with the disease’s severity and surgical outcomes. Incorporating the NMS-E into clinical practice could significantly enhance the management of endometriosis by addressing current diagnostic limitations and guiding surgical planning. Full article

The current standard oncotherapy for glioblastoma is limited by several adverse side effects, leading to a short-term patient survival rate paralleled by a worsening quality of life (QoL). Recently, Complementary and Integrative Medicine’s (CIM) innovative approaches have shown positive impacts in terms of better response to treatment, side effect reduction, and QoL improvement. In particular, promising potential in cancer therapy has been found in compounds coming from phyto- and mycotherapy. The objective of this study was to demonstrate the beneficial effects of a new phyto-mycotherapy supplement, named Ganostile, in the human glioblastoma cell line U251, in combination with chemotherapeutic agents, i.e., Cisplatin and a new platinum-based prodrug. Choosing a supplement dosage that mimicked oral supplementation in humans (about 1 g/day), through in vitro assays, microscopy, and cytometric analysis, it has emerged that the cells, after 48hr continuous exposure to Ganostile in combination with the chemical compounds, showed a higher mortality and a lower proliferation rate than the samples subjected to the different treatments administered individually. In conclusion, our data support the use of Ganostile in integrative oncology protocols as a promising adjuvant able to amplify conventional and new drug effects and also reducing resistance mechanisms often observed in brain tumors. Full article

Internet of Things (IoT) devices often operate with limited resources while interacting with users and their environment, generating a wealth of data. Machine learning models interpret such sensor data, enabling accurate predictions and informed decisions. However, the sheer volume of data from billions of devices can overwhelm networks, making traditional cloud data processing inefficient for IoT applications. This paper presents a comprehensive survey of recent advances in models, architectures, hardware, and design requirements for deploying machine learning on low-resource devices at the edge and in cloud networks. Prominent IoT devices tailored to integrate edge intelligence include Raspberry Pi, NVIDIA’s Jetson, Arduino Nano 33 BLE Sense, STM32 Microcontrollers, SparkFun Edge, Google Coral Dev Board, and Beaglebone AI. These devices are boosted with custom AI frameworks, such as TensorFlow Lite, OpenEI, Core ML, Caffe2, and MXNet, to empower ML and DL tasks (e.g., object detection and gesture recognition). Both traditional machine learning (e.g., random forest, logistic regression) and deep learning methods (e.g., ResNet-50, YOLOv4, LSTM) are deployed on devices, distributed edge, and distributed cloud computing. Moreover, we analyzed 1000 recent publications on “ML in IoT” from IEEE Xplore using support vector machine, random forest, and decision tree classifiers to identify emerging topics and application domains. Hot topics included big data, cloud, edge, multimedia, security, privacy, QoS, and activity recognition, while critical domains included industry, healthcare, agriculture, transportation, smart homes and cities, and assisted living. The major challenges hindering the implementation of edge machine learning include encrypting sensitive user data for security and privacy on edge devices, efficiently managing resources of edge nodes through distributed learning architectures, and balancing the energy limitations of edge devices and the energy demands of machine learning. Full article

Background: Patients with myeloproliferative neoplasms (MPNs) experience a high disease-related symptom burden. A specific instrument to evaluate quality of life (QoL), i.e., the MPN Symptom Assessment Form Total Symptom Score (MPN-SAF TSS; MPN-10), was developed. We conducted the translation, cultural adaptation, and validation into Romanian of the MPN-10. Methods: We translated the MPN-10 and tested its psychometric properties. Results: We recruited 180 MPN patients: 66 polycythemia vera (36.67%), 61 essential thrombocythemia (33.89%), 51 primary and secondary myelofibrosis (SMF) (28.33%), and 2 MPN-unclassifiable (1.11%). The mean TSS was 19.51 ± 16.51 points. Fatigue, inactivity, and concentration problems were the most cumbersome symptoms. We detected scoring differences between MPN subtypes regarding weight loss (p < 0.001), fatigue (p = 0.006), early satiety (p = 0.007), night sweats (p = 0.047), pruritus (p = 0.05), and TSS (p = 0.021). There were strong positive associations between TSS and inactivity, fatigue, and concentration problems, and moderate negative correlations between QoL scores and all MPN-10 items. Cronbach’s α internal consistency coefficient was 0.855. The Kaiser–Meyer–Olkin construct validity test result was 0.870 and the Bartlett Sphericity Test was significant (p < 0.001). Symptom scores were loaded into one single factor according to the exploratory factor analysis. Conclusions: The Romanian MPN-10 version displayed excellent psychometric properties and is a reliable instrument for assessing symptom burden and QoL in Romanian MPN patients. Full article

Rolando Toro’s Biodanza (SRT) is a therapeutic strategy that uses movement, music, and emotions to induce integrative living experiences. The present study aims to explore the efficacy of a three-month SRT intervention on motor, cognitive, and behavioral symptoms in patients with Parkinson’s disease (PD). This study employed a randomized between-group design. Twenty-eight non-demented PD patients were enrolled in this study. Out of these, fourteen patients were assigned to the active treatment group using the Biodanza SRT system and fourteen to the untreated control group. The study group attended 2 h SRT classes once a week, completing twelve lessons in twelve weeks. All patients underwent: (i) a neurological examination to measure the severity of motor symptoms, balance, mobility, and risk of falls, and (ii) a neuropsychological battery to assess cognitive status, apathy, depressive symptomatology, and perceived quality of life (QoL), at study entry (T0) and at twelve weeks (T1, end of dance training). At T1, we observed a significant improvement in motor (i.e., severity of motor symptoms and balance) and cognitive parameters (i.e., working memory and delayed verbal memory) in all treated patients compared with the controls. Furthermore, a significant improvement in the social support dimension was found in all treated patients compared to the controls. A trend toward increased apathy was found in untreated patients at T1. The three-month Biodanza intervention significantly ameliorated the motor parameters of PD patients, with a parallel improvement in cognitive and QoL status. Hence, Biodanza intervention can, in the short term, represent a useful personalized medical intervention for the management of Parkinson’s disease. Full article

Introduction: Due to the complex nature of chronic pain, especially in older adults, a biopsychosocial approach is more effective than an isolated approach for its management. Furthermore, when patients are actively engaged in their pain management, they are more likely to be successful than relying totally on others. Objective: To analyze the self-management strategies currently used by older adults with chronic pain. Method: An integrative review was conducted through seven online databases, searching for scientific studies on this topic published in the last 10 years. Results and conclusion: Fifty-eight studies were included in the final sample. Research on chronic pain self-management for older adults has increased in recent years. Although a diversity of chronic physical painful conditions are being investigated, many conditions are still under-investigated. Online and in-person strategies are currently adopted, demonstrating similar results. Positive results are evidenced by strategies including health promotion, mind control, social participation and take-action fields. Major results come from a combination of strategies focusing on biopsychosocial aspects of pain management. Results include not only the reduction of pain itself, but increased self-efficacy, adoption of health behaviors and improvement of functionality, among others, i.e., improved QoL, despite pain. Full article

Background: This study aimed to evaluate the relationship of selected clinical (i.e., body mass index, BMI) and psychological factors (i.e., anxiety, depression, and impulsiveness) with the quality of life (QoL) of elderly patients with cardiovascular disease (CVD) in a single clinical center in Italy. Methods: A total of 238 patients of older age (≥65 years) with CVD who voluntarily attended a single clinical center for weight loss and cardiac rehabilitation were sequentially recruited and tested upon admission to the hospital based on pre-established inclusion criteria. Results: The findings indicated that anxiety and depressive symptoms were moderately associated with lower QoL. Additionally, there were noteworthy but minor negative connections between impulsivity and QoL. Furthermore, BMI was inversely associated with the perceived QoL of the participants, and when incorporated into the regression analysis, BMI alone significantly accounted for 11.8% of the variability in QoL. This percentage increased to 18.4% with the inclusion of impulsiveness in the model and further to 34.3% with the addition of anxiety and depressive symptoms. However, after introducing anxiety and depression, the association between impulsivity and QoL ceased to be statistically significant. Conclusions: Integrating the routine assessment and treatment of psychological factors into the care of older patients with CVD is important for optimizing their overall health outcomes and improving their QoL. Full article

Background: Transcatheter edge-to-edge tricuspid valve repair (T-TEER) for tricuspid regurgitation (TR) is always guided by transesophageal echocardiography (TEE). As each patient has unique anatomy and acoustic window, adding transthoracic echocardiography (TTE) and cardiac CT could improve procedural planning and guidance. Objectives: We aimed to assess T-TEER success and outcomes of a personalized guidance approach, based on multimodality imaging (MMI) of patient-tailored four right-sided chamber views (four-right-ch), as depicted by CT, TTE, TEE and fluoroscopy. Methods: Patients were assigned to MMI or classical TEE guidance, depending on TTE acoustic window. In MMI patients, planning included cardiac CT, which determined the fluoroscopic angulations of the specific four-right-ch, while guidance relied heavily on TTE, with minimal intermittent TEE for leaflet grasping and result confirmation. Both TTE and TEE were matched to respective CT and fluoroscopy four-right-ch. TR severity and quality of life (QoL) parameters were assessed from baseline to 12 months. Results: A total of 40 T-TEER patients were included, with 17 procedures guided by MMI and 23 solely by TEE. Baseline characteristics were similar between groups, e.g., age (83.1 ± 4.1 vs. 81 ± 5.3, p = 0.182) or STS-Score (11.1 ± 7.4% vs. 10.6 ± 5.9%, p = 0.813). The primary efficacy endpoint of ≥one-grade TR reduction at 30 days was 94% (16/17) in MMI vs. 91% (21/23) in TEE patients, with two or more TR grade reduction in 65% vs. 52% (p = 0.793). Device success was overall 100%, with no device-related complications, but three TEE-associated cases of gastrointestinal bleeding in the TEE-only group. By 12 months, all 15 MMI and 19 TEE survivors improved NYHA functional class and QoL, e.g., Kansas City Cardiomyopathy Questionnaire Score Δ29.6 ± 6.7 vs. 21.9 ± 5.8 (p = 0.441) pts., 6-min walk distance Δ101.5 ± 36.4 vs. 85.7 ± 32.1 (p = 0.541) meters. Conclusions: In a subset of patients with good TTE acoustic window, MMI guidance of T-TEER is effective and seems to avoid gastroesophageal injuries caused by TEE probe manipulation. TR reduction, irrespective of guidance method, impacts long-term QoL. Full article