Effect of the cleaning and disinfection methods on the hygienic conditions of fermentation tanks of table olives (Olea europaea L.) Negrinha de Freixo cultivar.

This study aimed to evaluate and identify the microbial community attached to the surfaces of fermenter tanks used in table olive Negrinha de Freixo cultivar processing through molecular analysis and verify if the cleaning/disinfection was done correctly. Four fermentation tanks previously used in table olive processing were sampled at three different inside areas: upper, middle, and lower. Before sampling, four cleaning/disinfection methods were applied to the tanks, including (i) pressurised water; (ii) a disinfectant product used to clean bowls (Vasiloxe); (iii) 10% sodium hydroxide solution (caustic soda liquid); and (iv) a disinfectant product used by the wine industry (Hosbit). For each sample collected, mesophilic aerobic bacteria, yeast and moulds (YMC), lactic acid bacteria (LAB), as well as total coliforms (TC) and Pseudomonas aeruginosa were evaluated. The results showed significant differences between the different cleaning/disinfection methods applied. The fermenter sanitised with only pressurised water showed a greater abundance of microorganisms than the others. Mesophilic aerobic bacteria were the predominant population, with counts ranging between 2.63 and 5.56 log10 CFU/100 cm2, followed by the moulds (3.11-5.03 log10 CFU/100 cm2) and yeasts (2.42-5.12 log10 CFU/100 cm2). High diversity of microbial communities was observed between the different fermenter tanks. The most abundant species belonged to Aureobasidium, Bacillaceae, Cladosporium, and Rhodotorula genera. LAB, TC, and P. aeruginosa were not detected. This study hopes to improve hygienic conditions and increase the quality assurance and safety of the final product.

Application of the FTIR technique as a non-invasive tool to discriminate Portuguese olive oils with Protected Designation of Origin.

Three Portuguese olive oils with PDO ('Azeite do Alentejo Interior', 'Azeites da Beira Interior' and 'Azeite de Trás-os-Montes') were studied considering their physicochemical quality, antioxidant capacity, oxidative stability, total phenols content, gustatory sensory sensations and Fourier transform infrared (FTIR) spectra. All oils fulfilled the legal thresholds of EVOOs and the PDO's specifications. Olive oils from 'Azeite da Beira Interior' and 'Azeite de Trás-os-Montes' showed greater total phenols contents and antioxidant capacities, while 'Azeites da Beira Interior' presented higher oxidative stabilities. Linear discriminant models were developed using FTIR spectra (transmittance and the 1st and 2nd derivatives), allowing the correct identification of the oils' PDO (100 % sensitivity and specificity, repeated K-fold-CV). This study also revealed that multiple linear regression models, based on FTIR transmittance data, could predict the sweet, bitter, and pungent intensities of the PDO oils (R2 ≥0.979±0.016; RMSE≤0.26±0.05, repeated K-fold-CV). This demonstrates the potential of using FTIR as a non-destructive technique for authenticating oils with PDO.

Optical Flow-Based Obstacle Detection for Mid-Air Collision Avoidance.

The sky may seem big enough for two flying vehicles to collide, but the facts show that mid-air collisions still occur occasionally and are a significant concern. Pilots learn manual tactics to avoid collisions, such as see-and-avoid, but these rules have limitations. Automated solutions have reduced collisions, but these technologies are not mandatory in all countries or airspaces, and they are expensive. These problems have prompted researchers to continue the search for low-cost solutions. One attractive solution is to use computer vision to detect obstacles in the air due to its reduced cost and weight. A well-trained deep learning solution is appealing because object detection is fast in most cases, but it relies entirely on the training data set. The algorithm chosen for this study is optical flow. The optical flow vectors can help us to separate the motion caused by camera motion from the motion caused by incoming objects without relying on training data. This paper describes the development of an optical flow-based airborne obstacle detection algorithm to avoid mid-air collisions. The approach uses the visual information from a monocular camera and detects the obstacles using morphological filters, optical flow, focus of expansion, and a data clustering algorithm. The proposal was evaluated using realistic vision data obtained with a self-developed simulator. The simulator provides different environments, trajectories, and altitudes of flying objects. The results showed that the optical flow-based algorithm detected all incoming obstacles along their trajectories in the experiments. The results showed an F-score greater than 75% and a good balance between precision and recall.

Systematic Review of Emotion Detection with Computer Vision and Deep Learning.

Emotion recognition has become increasingly important in the field of Deep Learning (DL) and computer vision due to its broad applicability by using human-computer interaction (HCI) in areas such as psychology, healthcare, and entertainment. In this paper, we conduct a systematic review of facial and pose emotion recognition using DL and computer vision, analyzing and evaluating 77 papers from different sources under Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our review covers several topics, including the scope and purpose of the studies, the methods employed, and the used datasets. The scope of this work is to conduct a systematic review of facial and pose emotion recognition using DL methods and computer vision. The studies were categorized based on a proposed taxonomy that describes the type of expressions used for emotion detection, the testing environment, the currently relevant DL methods, and the datasets used. The taxonomy of methods in our review includes Convolutional Neural Network (CNN), Faster Region-based Convolutional Neural Network (R-CNN), Vision Transformer (ViT), and "Other NNs", which are the most commonly used models in the analyzed studies, indicating their trendiness in the field. Hybrid and augmented models are not explicitly categorized within this taxonomy, but they are still important to the field. This review offers an understanding of state-of-the-art computer vision algorithms and datasets for emotion recognition through facial expressions and body poses, allowing researchers to understand its fundamental components and trends.

Predicting hospital emergency department visits accurately: A systematic review.

OBJECTIVES: The emergency department (ED) is a very important healthcare entrance point, known for its challenging organisation and management due to demand unpredictability. An accurate forecast system of ED visits is crucial to the implementation of better management strategies that optimise resources utilization, reduce costs and improve public confidence. The aim of this review is to investigate the different factors that affect the ED visits forecasting outcomes, in particular the predictive variables and type of models applied. METHODS: A systematic search was conducted in PubMed, Web of Science and Scopus. The review methodology followed the PRISMA statement guidelines. RESULTS: Seven studies were selected, all exploring predictive models to forecast ED daily visits for general care. MAPE and RMAE were used to measure models' accuracy. All models displayed good accuracy, with errors below 10%. CONCLUSIONS: Model selection and accuracy was found to be particularly sensitive to the ED dimension. While ARIMA-based and other linear models have good performance for short-time forecast, some machine learning methods proved to be more stable when forecasting multiple horizons. The inclusion of exogenous variables was found to be advantageous only in bigger EDs.

A Real-Time Automated Defect Detection System for Ceramic Pieces Manufacturing Process Based on Computer Vision with Deep Learning.

Defect detection is a key element of quality control in today's industries, and the process requires the incorporation of automated methods, including image sensors, to detect any potential defects that may occur during the manufacturing process. While there are various methods that can be used for inspecting surfaces, such as those of metal and building materials, there are only a limited number of techniques that are specifically designed to analyze specialized surfaces, such as ceramics, which can potentially reveal distinctive anomalies or characteristics that require a more precise and focused approach. This article describes a study and proposes an extended solution for defect detection on ceramic pieces within an industrial environment, utilizing a computer vision system with deep learning models. The solution includes an image acquisition process and a labeling platform to create training datasets, as well as an image preprocessing technique, to feed a machine learning algorithm based on convolutional neural networks (CNNs) capable of running in real time within a manufacturing environment. The developed solution was implemented and evaluated at a leading Portuguese company that specializes in the manufacturing of tableware and fine stoneware. The collaboration between the research team and the company resulted in the development of an automated and effective system for detecting defects in ceramic pieces, achieving an accuracy of 98.00% and an F1-Score of 97.29%.

Patterns of adult and youth inpatient admissions before and after the COVID-19 pandemic in a psychiatric ward: an observational study.

BACKGROUND: The current pandemic situation led to deep changes not only in social relationships, but also on clinical care and access to healthcare facilities. The authors aimed to understand whether this context affected the main characteristics of psychiatric hospitalizations, measured by admissions in a portuguese acute psychiatric ward. METHODS: Retrospective data collection of all patients admitted in Centro Hospitalar Psiquiátrico de Lisboa, in two different time periods: pre-COVID-19 (march 11th, 2019 to march 10th, 2020, n = 1845) and COVID-19 (march 11th, 2020 to march 10th, 2021, n = 1278); comparing the number of total admissions, compulsory ones, age, sex, median days of admission, median days to readmission and diagnosis at discharge. Distribution of disorders in both groups, as well as in compulsory admissions were also evaluated. The same comparisons were evaluated in the 15-25-year-old patient group. RESULTS: Statistical significance was found regarding total number of admissions (reduction of around 30.7%), as well as compulsory ones (reduction of 14%, although the relative frequency had increased), days of admission and distribution between admissions (with lower reductions regarding dementias, schizophrenia and affective disorders, while substance use disorders and intellectual disabilities presented reductions of over 50%), with no differences between gender, median age, previous admissions or readmissions. Distribution between compulsory admissions did not present differences before and during COVID periods. For patients between 15 and 25 years of age, statistical significance was found regarding total number of compulsory ones (94 versus 44, p-value = 0.01), and in all groups of diagnoses (all with p-value = 0.001). CONCLUSIONS: While there was a general reduction in the overall number of patients admitted, in the most severe conditions (compulsory admissions and schizophrenia diagnosis) did not present such a reduction. Difficulties in social, clinical and family networks can explain the reduction of the time to readmission. Future research could show whether there is a rebound increase number of admissions in the other diagnoses. TRIAL REGISTRATION: The current study was approved by the hospital's scientific and ethics committees (CCP number 0060/2021 and CES 09/2021).

An Electronic Nose as a Non-Destructive Analytical Tool to Identify the Geographical Origin of Portuguese Olive Oils from Two Adjacent Regions.

The geographical traceability of extra virgin olive oils (EVOO) is of paramount importance for oil chain actors and consumers. Oils produced in two adjacent Portuguese regions, Côa (36 oils) and Douro (31 oils), were evaluated and fulfilled the European legal thresholds for EVOO categorization. Compared to the Douro region, oils from Côa had higher total phenol contents (505 versus 279 mg GAE/kg) and greater oxidative stabilities (17.5 versus 10.6 h). The majority of Côa oils were fruity-green, bitter, and pungent oils. Conversely, Douro oils exhibited a more intense fruity-ripe and sweet sensation. Accordingly, different volatiles were detected, belonging to eight chemical families, from which aldehydes were the most abundant. Additionally, all oils were evaluated using a lab-made electronic nose, with metal oxide semiconductor sensors. The electrical fingerprints, together with principal component analysis, enabled the unsupervised recognition of the oils' geographical origin, and their successful supervised linear discrimination (sensitivity of 98.5% and specificity of 98.4%; internal validation). The E-nose also quantified the contents of the two main volatile chemical classes (alcohols and aldehydes) and of the total volatiles content, for the studied olive oils split by geographical origin, using multivariate linear regression models (0.981 ≤ R2 ≤ 0.998 and 0.40 ≤ RMSE ≤ 2.79 mg/kg oil; internal validation). The E-nose-MOS was shown to be a fast, green, non-invasive and cost-effective tool for authenticating the geographical origin of the studied olive oils and to estimate the contents of the most abundant chemical classes of volatiles.

Pickering Emulsions Stabilized with Curcumin-Based Solid Dispersion Particles as Mayonnaise-like Food Sauce Alternatives.

Pickering emulsions, which are emulsions stabilized by colloidal particles, are being increasingly positioned as novel strategies to develop innovative food product solutions. In this context, the present work aims to develop Pickering emulsions stabilized by natural-based curcumin-loaded particles produced by the solid dispersion technique as promising mayonnaise-like food sauce alternatives. Two particle formulations (KC1 and KC2) were produced using k-carrageenan as the matrix material and different curcumin contents, then employed in the preparation of three Pickering emulsion formulations comprising different oil fractions (φ) and particle concentrations (KC1 φ 0.4 (4.7%), KC2 φ 0.4 (4.7%) and KC2 φ 0.6 (4.0%)). The creaming index tests accompanied by the optical microscopy analysis evidenced the good stability of the developed products for the tested period of 28 days. The final products were tested concerning color attributes, pH, oxidative stability, textural, and nutritional composition, and compared with two commercial mayonnaises (traditional and light products). Overall, the produced emulsions were characterized by a bright yellow color (an appealing attribute for consumers), an acidic pH (similar to mayonnaise), and a considerably improved oxidative stability, implying a foreseeable longer shelf life. The sauce KC1 φ 0.4 (4.7%) showed a similar texture to the light commercial mayonnaise, being a promising alternative to conventional sauces, holding a low-fat content and potentially added benefits due to the curcumin and virgin olive oil intrinsic properties.

Design, Synthesis and SAR in 2,4,7-Trisubstituted Pyrido[3,2-d]Pyrimidine Series as Novel PI3K/mTOR Inhibitors.

This work describes the synthesis, enzymatic activities on PI3K and mTOR, in silico docking and cellular activities of various uncommon 2,4,7 trisubstituted pyrido[3,2-d]pyrimidines. The series synthesized offers a chemical diversity in C-7 whereas C-2 (3-hydroxyphenyl) and C-4 groups (morpholine) remain unchanged, in order to provide a better understanding of the molecular determinants of PI3K selectivity or dual activity on PI3K and mTOR. Some C-7 substituents were shown to improve the efficiency on kinases compared to the 2,4-di-substituted pyrimidopyrimidine derivatives used as references. Six novel derivatives possess IC50 values on PI3Kα between 3 and 10 nM. The compounds with the best efficiencies on PI3K and mTOR induced micromolar cytotoxicity on cancer cell lines possessing an overactivated PI3K pathway.

Application of AR and VR in hand rehabilitation: A systematic review.

BACKGROUND: The human hand is the part of the body most frequently injured in work related accidents, accounting for a third of all accidents at work and often involving surgery and long periods of rehabilitation. Several applications of Augmented Reality (AR) and Virtual Reality (VR) have been used to improve the rehabilitation process. However, there is no sound evidence about the effectiveness of such applications nor the main drivers of therapeutic success. OBJECTIVES: The objective of this study was to review the efficacy of AR and VR interventions for hand rehabilitation. METHODS: A systematic search of publications was conducted in October 2019 in IEEE Xplore, Web of Science, Cochrane library, and PubMed databases. Search terms were: (1) video game or videogame, (2) hand, (3) rehabilitation or therapy and (4) VR or AR. Articles were included if (1) were written in English, (2) were about VR or AR applications, (3) were for hand rehabilitation, (4) the intervention had tests on at least ten patients with injuries or diseases which affected hand function and (5) the intervention had baseline or intergroup comparisons (AR or VR intervention group versus conventional physical therapy group). PRISMA protocol guidelines were followed to filter and assess the articles. RESULTS: From the eight selected works, six showed improvements in the intervention group, and two no statistical differences between groups. We were able to identify motivators of patients' adherence, namely real-time feedback to the patients, challenge, and increased individualized difficulty. Automated tracking, easy integration in the home setting and the recording of accurate metrics may increase the scalability and facilitate healthcare professionals' assessments. CONCLUSIONS: This systematic review provided advantages and drivers for the success of AR/VR application for hand rehabilitation. The available evidence suggests that patients can benefit from the use of AR or VR interventions for hand rehabilitation.

Psychosocial drivers for change: Understanding and promoting stakeholder engagement in local adaptation to climate change in three European Mediterranean case studies.

Stakeholder engagement in the processes of planning local adaptation to climate change faces many challenges. The goal of this work was to explore whether or not the intention of engaging could be understood (Study 1) and promoted (Study 2), by using an extension of the theory of planned behaviour. In Study 1, stakeholders from three European Mediterranean case studies were surveyed: Baixo Vouga Lagunar (Portugal), SCOT Provence Méditerranée (France), and the island of Crete (Greece) (N = 115). Stakeholders' intention of engaging was significantly predicted by subjective norm (which was predicted by injunctive normative beliefs towards policy-makers and stakeholders) and by perceived behavioural control (which was predicted by knowledge of policy and instruments). Study 2 was conducted in the Baixo Vouga Lagunar case study and consisted of a two-workshop intervention where issues on local and regional adaptation, policies, and engagement were presented and discussed. A within-participants comparison of initial survey results with results following the workshops (NT1 = 12, NT2 = 15, NT3 = 12) indicated that these were successful in increasing stakeholders' intention of engaging. This increase was paired with a) an increase in injunctive normative beliefs towards policy-makers and consequently in subjective norm, and to b) a decrease in perceived complexity of planning local adaptation and an increase in knowledge regarding adaptation to climate change.

Assessment of Laparoscopic Skills Performance: 2D Versus 3D Vision and Classic Instrument Versus New Hand-Held Robotic Device for Laparoscopy.

INTRODUCTION AND OBJECTIVES: Laparoscopic surgery has undeniable advantages, such as reduced postoperative pain, smaller incisions, and faster recovery. However, to improve surgeons' performance, ergonomic adaptations of the laparoscopic instruments and introduction of robotic technology are needed. The aim of this study was to ascertain the influence of a new hand-held robotic device for laparoscopy (HHRDL) and 3D vision on laparoscopic skills performance of 2 different groups, naïve and expert. MATERIALS AND METHODS: Each participant performed 3 laparoscopic tasks-Peg transfer, Wire chaser, Knot-in 4 different ways. With random sequencing we assigned the execution order of the tasks based on the first type of visualization and laparoscopic instrument. Time to complete each laparoscopic task was recorded and analyzed with one-way analysis of variance. RESULTS: Eleven experts and 15 naïve participants were included. Three-dimensional video helps the naïve group to get better performance in Peg transfer, Wire chaser 2 hands, and Knot; the new device improved the execution of all laparoscopic tasks (P < .05). For expert group, the 3D video system benefited them in Peg transfer and Wire chaser 1 hand, and the robotic device in Peg transfer, Wire chaser 1 hand, and Wire chaser 2 hands (P < .05). CONCLUSION: The HHRDL helps the execution of difficult laparoscopic tasks, such as Knot, in the naïve group. Three-dimensional vision makes the laparoscopic performance of the participants without laparoscopic experience easier, unlike those with experience in laparoscopic procedures.

Extending the understanding of the impact of conscientiousness on individual soccer performance: examining the mediating role of mental toughness.

BACKGROUND: Drawing upon Motowidlo et al.'s theory of individual differences in individual performance, the current study aims to contribute to a better understanding of the relationship between conscientiousness and individual soccer performance, by examining whether mental toughness, posited as a characteristic adaptation, acts as a psychological mechanism underlying this link. PARTICIPANTS AND PROCEDURE: Relying upon a concurrent validity design, 130 soccer players completed a survey including the measures of conscientiousness and mental toughness. Participants were also instructed to provide a subjective assessment of their individual soccer performance, by self-rating their physical, technical and tactical performance levels. Their objective performance was also measured as the total amount of minutes each player participated in official games, during the first half-season. RESULTS: The findings showed that conscientiousness and mental toughness represent significant and meaningful predictors of both individual soccer performance measures gathered, i.e. individual soccer subjective and objective performance. As expected, further mediation analyses showed that the influence of conscientiousness on subjective performance is totally indirect, via mental toughness. Still, for the objective performance criterion, only the direct effect of conscientiousness was supported. CONCLUSIONS: These findings support the merits of conscientiousness as a valid predictor of human performance across achievement contexts, namely in sports settings and specifically in the domain of soccer. They also suggest that while this personality factor exerts a direct impact on individual soccer objective performance, it seems to play a more distal influence on subjective performance, by enacting individual mental toughness resources. Major theoretical and applied research implications are discussed.

Effect of photostimulation through red LED light radiation on natural fermentation of table olives: An innovative case study with Negrinha the Freixo variety.

In this study, for the first time, red LED light radiation was applied to the fermentation process of table olives using the Negrinha de Freixo variety. Photostimulation using LED light emission (630 ± 10 nm) is proposed to shorten and speed up this stage and reduce time to market. Several physical-chemical characteristics and microorganisms (total microbial count of mesophilic aerobic, molds, yeasts, and lactic acid bacteria) and their sequence during fermentation were monitored. The fermentation occurred for 122 days, with two irradiation periods for red LED light. The nutritional composition and sensory analysis were performed at the end of the process. Fermentation under red LED light increased the viable yeast and lactic acid bacteria (LAB) cell counts and decreased the total phenolics in olives. Even though significant differences were observed in some color parameters, the hue values were of the same order of magnitude and similar for both samples. Furthermore, the red LED light did not play a relevant change in the texture profile, preventing the softening of the fruit pulp. Similarly, LED light did not modify the existing type of microflora but increased species abundance, resulting in desirable properties and activities. The species identified were yeasts - Candida boidinii, Pichia membranifaciens, and Saccharomyces cerevisiae, and bacteria - Lactobacillus plantarum and Leuconostoc mesenteroides, being the fermentative process dominated by S. cerevisiae and L. plantarum. At the end of fermentation (122 days), the irradiated olives showed less bitterness and acidity, higher hardness, and lower negative sensory attributes than non-irradiated. Thus, the results of this study indicate that red LED light application can be an innovative technology for table olives production.

Positive Youth Development, Mental Stress and Life Satisfaction in Middle School and High School Students in Portugal: Outcomes on Stress, Anxiety and Depression.

The relation between positive youth development and stress, anxiety and depression was studied considering the mediator role of psychological symptoms and life satisfaction. A total of 3109 students included in the "Psychological Health and Well-being" study of the School Observatory participated, including 1618 females and 1491 males aged between 11 and 18 years old (M = 14.45; SD = 1.88), belonging to different school groups in different regions of the country. Adolescents with higher stress, depression and anxiety levels reported lower levels of competence, confidence and connection, as well as more psychological symptoms and lower life satisfaction. The results also showed that adolescents with higher levels of competence, confidence and connection reported less psychological symptoms and more life satisfaction. Two separate mediation analyses were performed to analyse the role of mental distress and life satisfaction on the relationship between positive youth development indicators and stress, anxiety and depression. These analyses confirmed the predicted relationships and partial mediations between mental distress and life satisfaction. These results should be taken into account in public policies concerning young people's health and education that should involve both targeted and indicated prevention strategies, including school and community-based interventions, in order to be effective.

Analysis of domain shift in whole prostate gland, zonal and lesions segmentation and detection, using multicentric retrospective data.

Despite being one of the most prevalent forms of cancer, prostate cancer (PCa) shows a significantly high survival rate, provided there is timely detection and treatment. Computational methods can help make this detection process considerably faster and more robust. However, some modern machine-learning approaches require accurate segmentation of the prostate gland and the index lesion. Since performing manual segmentations is a very time-consuming task, and highly prone to inter-observer variability, there is a need to develop robust semi-automatic segmentation models. In this work, we leverage the large and highly diverse ProstateNet dataset, which includes 638 whole gland and 461 lesion segmentation masks, from 3 different scanner manufacturers provided by 14 institutions, in addition to other 3 independent public datasets, to train accurate and robust segmentation models for the whole prostate gland, zones and lesions. We show that models trained on large amounts of diverse data are better at generalizing to data from other institutions and obtained with other manufacturers, outperforming models trained on single-institution single-manufacturer datasets in all segmentation tasks. Furthermore, we show that lesion segmentation models trained on ProstateNet can be reliably used as lesion detection models.

Collecting system percutaneous access using real-time tracking sensors: first pig model in vivo experience.

PURPOSE: Precise needle puncture of the renal collecting system is an essential but challenging step for successful percutaneous nephrolithotomy. We evaluated the efficiency of a new real-time electromagnetic tracking system for in vivo kidney puncture. MATERIALS AND METHODS: Six anesthetized female pigs underwent ureterorenoscopy to place a catheter with an electromagnetic tracking sensor into the desired puncture site and ascertain puncture success. A tracked needle with a similar electromagnetic tracking sensor was subsequently navigated into the sensor in the catheter. Four punctures were performed by each of 2 surgeons in each pig, including 1 each in the kidney, middle ureter, and right and left sides. Outcome measurements were the number of attempts and the time needed to evaluate the virtual trajectory and perform percutaneous puncture. RESULTS: A total of 24 punctures were easily performed without complication. Surgeons required more time to evaluate the trajectory during ureteral than kidney puncture (median 15 seconds, range 14 to 18 vs 13, range 11 to 16, p=0.1). Median renal and ureteral puncture time was 19 (range 14 to 45) and 51 seconds (range 45 to 67), respectively (p=0.003). Two attempts were needed to achieve a successful ureteral puncture. The technique requires the presence of a renal stone for testing. CONCLUSIONS: The proposed electromagnetic tracking solution for renal collecting system puncture proved to be highly accurate, simple and quick. This method might represent a paradigm shift in percutaneous kidney access techniques.

Notes on the husbandry and long-term transportation of Bull ray (Pteromylaeus bovinus) and Dolphinfish (Coryphaena hippurus and Coryphaena equiselis).

Bull rays (Pteromylaeus bovinus) and Dolphinfish (Coryphaena hippurus and Coryphaena equiselis) were collected in Olhão (south of Portugal). These animals hosted multiple parasites, namely Caligus spp., and underwent a variety of treatments to remove them. Of all treatments tested, hydrogen peroxide showed the best results, although only concentrations above 100 ppm were effective in parasite removal. These high concentrations, however, proved to be highly toxic for the fish and led to the loss of some animals, especially those which had been handled before treatment. A total of 14 Bull rays were transported to Bolougne-Sur-Mer (France) by road and some animals were lost, which was attributed to excessive time in transit (>45 hr). In another transport, three Bull rays and 10 Dolphinfishes were moved to Stralsund (Germany) by road and air. The mechanical wounds suffered by one of the Bull rays during transport led to its death and, consequently, a deterioration of water quality in the tank containing two other conspecifics. This deterioration of water quality resulted in problems for the other two Bull rays, and one perished approximately 48 hr after arrival. The authors concluded that Dolphinfish can be transported with a low bioload for at least 27 hr, and Bull rays should not undergo transports longer than 35 hr. Special attention must be taken to injured animals, since this can lead to a decrease in water quality and consequently affect other animals in the same transport tank.

Public-Private Partnerships Model Applied to Hospitals-A Critical Review.

In this paper, a conceptual framework for investigating the PPP model as it relates to hospitals is proposed. When the PPP model is applied to healthcare (hospitals), it is possible to discover the path to success by developing a critical assessment and deriving a clear model. It is concluded that most PPP model implementations in hospitals around the world have produced favorable outcomes, both in terms of the performance of healthcare units and in terms of cost-effectiveness. Additionally, a path-to-success model that applies to hospitals is offered, taking into account six PPP model dimensions: (i) Environment; (ii) Potentiate Benefits; (iii) Constant Measure; (iv) Evaluation; (v) Management; and (vi) Enhance Strengths. The PPP model only applies case by case and under specific requirements that should be met cumulatively to provide additional value to healthcare's quality of service. The right conditions are created, the right benefits are amplified, public concerns are frequently assessed, private contributions are carefully considered, and all pressing challenges are managed by enhancing both public and private strengths. Leading decision- and action-making processes in corporate, governmental, and social sectors is the goal of managing PPP models.