Validation Study of the Spanish Version of the Measure of Happiness (MH) Questionnaire

This study aims to validate the Spanish version of the Measure of Happiness (MH), a questionnaire that identifies the specific areas of an individual’s life that are related to experienced happiness. The sample consisted of 458 Spanish native speakers (65.7% women, 34.3% men; mean age = 24.14, SD = 8.45) and was divided into two groups: Sample 1 (N = 226) underwent Exploratory Factor Analysis (EFA), and Sample 2 (N = 232) underwent Confirmatory Factor Analysis (CFA). The convergent and discriminant validity of the Spanish version of the MH and its subscales was assessed by calculating Pearson correlations between the MH factors and the Subjective Happiness Scale, the State–Trait Anxiety Inventory, the Beck Depression Inventory, and the WHOQOL-BREF. The EFA and CFA confirmed the original five-factor structure of the MH questionnaire. The only difference in the Spanish version of the MH is that Item 4, which was originally assigned to Factor 2 “Financial Status”, was reallocated to Factor 1 “Psychophysical Status”. The reliability of the Spanish version of the MH questionnaire was also confirmed, and the factors correlated in the expected direction with the constructs of quality of life, happiness, anxiety, and depression. The MH questionnaire demonstrated excellent psychometric properties among Spanish respondents

Pick-up & Deliver in Maintenance Management of Renewable Energy Power Plants

Logistic optimization is a strategic element in many industrial processes, given that an optimized logistics makes the processes more efficient. A relevant case, in which the optimization of logistics can be decisive, is the maintenance in a Wind Farm where it can lead directly to a saving of energy cost. Wind farm maintenance presents, in fact, significant logistical challenges. They are usually distributed throughout the territory and also located at considerable distances from each other, they are generally found in places far from uninhabited centers and sometimes difficult to reach and finally spare parts are rarely available on the site of the plant itself. In this paper, we will study the problem concerning the optimization of maintenance logistics of wind plants based on the use of specific vehicle routing optimization algorithms. In particular a pickup-and-delivery algorithm with time-window is adopted to satisfy the maintenance requests of these plants, reducing their management costs. The solution was applied to a case study in a renewable energy power plant. Results time reduction and simplification and optimization obtained in the real case are discussed to evaluate the effectiveness and efficiency of the adopted approach

The impact of face masks used for COVID-19 prevention on emotion recognition in facial expressions: an experimental study

This study aimed to evaluate the impact of face masks used for COVID-19 prevention on emotion recognition in facial expressions. Seventy-two (72) adult participants (48 females, 24 males) attempted to correctly identify different emotions displayed by a female and a male actor’s facial expressions. Simulated emotions included neutrality, happiness, surprise, disgust, sadness, fear, and anger at two levels of intensity, with or without wearing a surgical mask. Accuracy rates of facial expression recognition and response times were collected. The GLM analysis for accuracy revealed a main effect of emotions (F(5,350)=57.47, P<.001) and face masks (without>with) (F(1,70)=338.95, P<.001), as well as a three-way interaction between emotions, masks, and actors (F(5,350)=9.69, P<.001). Disgust was the least recognized emotion, followed by sadness, while hap- piness, anger and surprise were the easiest to identify. The analysis of response times suggested that, when partially covered by a mask, facial expressions can be more ambiguous and difficult to read, and a larger amount of time was required to provide a response. In line with results on accu- racy, sadness was generally the most difficult emotion to identify. Male and female participants had similar response times. Globally, these results show that wearing masks can significantly reduce the ability to detect emotions in facial expressions. However, when emotions are expressed at higher intensity levels, this effect may be mitigate

Machine-Learning-Based Tool to Predict Target Prostate Biopsy Outcomes: An Internal Validation Study

Abstract: The aim of this study is to present a personalized predictive model (PPM) with a machine learning (ML) system that is able to identify and classify patients with suspected prostate cancer (PCa) following mpMRI. We extracted all the patients who underwent fusion biopsy (FB) from March 2014 to December 2019, while patients from August 2020 to April 2021 were included as a validation set. The proposed system was based on the following four ML methods: a fuzzy inference system (FIS), the support vector machine (SVM), k-nearest neighbors (KNN), and self-organizing maps (SOMs). Then, a system based on fuzzy logic (FL) + SVM was compared with logistic regression (LR) and standard diagnostic tools. A total of 1448 patients were included in the training set, while 181 patients were included in the validation set. The area under the curve (AUC) of the proposed FIS + SVM model was comparable with the LR model but outperformed the other diagnostic tools. The FIS + SVM model demonstrated the best performance, in terms of negative predictive value (NPV), on the training set (78.5%); moreover, it outperformed the LR in terms of specificity (92.1% vs. 83%). Considering the validation set, our model outperformed the other methods in terms of NPV (60.7%), sensitivity (90.8%), and accuracy (69.1%). In conclusion, we successfully developed and validated a PPM tool using the FIS + SVM model to calculate the probability of PCa prior to a prostate FB, avoiding useless ones in 15% of the cases

Association Between Palliative Care and Patient and Caregiver Outcomes: A Systematic Review and Meta-analysis

The use of palliative care programs and the number of trials assessing their effectiveness have increased

Practice patterns and 90-day treatment-related morbidity in early-stage cervical cancer

To evaluate the impact of the Laparoscopic Approach to Cervical Cancer (LACC) Trial on patterns of care and surgery-related morbidity in early-stage cervical cancer

The Impact of Face Masks Used for COVID-19 Prevention on Emotion Recognition in Facial Expressions: An Experimental Study

This study aimed to evaluate the impact of face masks used for COVID-19 prevention on emotion recognition in facial expressions. Seventy-two (72) adult participants (48 females, 24 males) attempted to correctly identify different emotions displayed by a female and a male actor’s facial expressions. Simulated emotions included neutrality, happiness, surprise, disgust, sadness, fear, and anger at two levels of intensity, with or without wearing a surgical mask. Accuracy rates of facial expression recognition and response times were collected. The GLM analysis for the accuracy revealed a main effect of emotions (F (5.350) = 57.47, p < 0.001) and face masks (without > with) (F (1.70) = 338.95, p < 0.001), as well as a three-way interaction between emotions, masks, and actors (F (5.350) = 9.69, p < 0.001). Disgust was the least recognized emotion, followed by sadness, while happiness, anger, and surprise were the easiest to identify. The analysis of the response times suggested that, when partially covered by a mask, facial expressions can be more ambiguous and difficult to read, and a larger amount of time was required to provide a response. In line with the results on accuracy, sadness was generally the most difficult emotion to identify. Male and female participants had similar response times. Globally, these results show that wearing masks can significantly reduce the ability to detect emotions in facial expressions. However, when emotions are expressed at higher intensity levels, this effect may be mitigated

Robotic Off-Clamp Simple Enucleation Single-Layer Renorrhaphy Partial Nephrectomy (ROSS): Surgical Insights after an Initial Experience

Robotic technology allows the beginner surgeon to approach minimally-invasive partial nephrectomy (PN) avoiding the otherwise long learning curve of pure laparoscopy. The present video-article reported the surgical technique and the outcomes of the first 11 cases performed by a young surgeon starting with the experience of robotic PN. Transperitoneal robotic PN, with an off-clamp approach, a simple enucleation technique, and a single-layer medullar renorrhaphy was performed uneventfully in all cases but one, with comparable outcomes to the available literature. With the present experience, we are trying to give the reader a different point of view of the current knowledge. In our series, off-clamp robotic PN was not chosen while looking for a better functional outcome, but rather as a “forced” choice within the specific “in training” setting the interventions were performed in. We underline how the off-clamp approach was the way to cut out the potential for vascular complications derived from the application/removal of the clamp itself on the renal artery. Indeed, when Scanlan bulldogs are not available, one of the limits of robotic PN is that the first surgeon is not autonomous in placing/removing the clamp. We found that tumour enucleation resection technique had the perfect synergistic effect in maximizing the perioperative vision, and thus the safety, notwithstanding the clampless approach

Field performance of Trelleborg PneuTrac tyres

Tractors have become heavier and more powerful, so bigger tyres are necessary to the exert adequate traction forces and to limit the soil compaction. Nevertheless, in the last 50 years, wheel load has increased more than twice the tyre-soil contact area, consequently, soil compaction caused by tractors has been increased as well. A tractor equipped with Trelleborg PneuTrac tyres could be an exception to this trend, because these tyres can attain large tyre flexibility, so that they allow a larger tyre footprint and lower inflating pressure than any standard tyre. The aim of this paper was the drawbar performance comparison between a set of PneuTrac tyres and a set of equivalent radial tyres with the same external drawing. Both of these tyres were mounted in two 115 kW tractors with the same mass configuration. On each tractor, a load cell was installed in order to measure the drawbar pull and a CAN-Bus data logger was fitted to measure the vehicle operating parameters. Drawbar tests were carried out with the two tractors in the same soil at different water contents. From the acquired data, the drawbar pull and the efficiency were calculated. The obtained results demonstrate that Trelleborg PneuTrac permits to increase the drawbar pull up to 5.7% and to reduce the slip. Moreover, its performance was slightly less affected by the soil conditions