DIVISIONALIZATION IN VERTICAL STRUCTURES

We study the incentives to create divisions by a firm once it is taken into account the vertical structures of an industry. Downstream firms, that must buy an essential input to upstream firms, may create divisions. Divisionalization reduces their bargaining power against upstream firms. This effect must be weighted against the usual incentive to divisionalize, namely the increase in the share of the final market that a firm obtains through it. We show that incentives to divisonalize are severely reduced when compared with the standard results, and that even sometimes firms choose not to divisionalize at all. The paper also shows the implications of the former analysis on the internal organization of firms and on the incentives to vertically integrate.

Divisionalization in vertical structures

We evaluate the incentives to create within-industry independent divisions once thevertical structure of the industry is considered. Divisionalization allows a firm to gainmarket share in the final market, but it also leads to an increase in total payments tothe input supplier. The less competitive the upstream market, the more important thesecond effect will be, and this reduces the profitability of divisionalization. As aconsequence, a less competitive upstream segment leads to a lower total number ofdivisions in equilibrium and a less competitive final market, harming end consumerswho will face higher prices.Funding for open access charge: Universidad de Málaga / CBUA. Conselleria d'Educació, Investigació, Cultura i Esport, Grant/Award Number: Prometeo/2021/073; Spanish Ministry of Economy and Innovation, Grant/Award Numbers: PID 2020-115018RB-C33, PID2021-127736NB-I00, PID2022-142356NB-I00

Internalizing and externalizing personality and subjective effects in a sample of adolescent cannabis users

Cannabis is the illicit substance most widely used by adolescents. Certain personality traits such as impulsivity and sensation seeking, and the subjective effects experienced after substance use (e.g. euphoria or relaxation) have been identified as some of the main etiological factors of consumption. This study aims to categorize a sample of adolescent cannabis users based on their most dominant personality traits (internalizing and externalizing profile). Then, to make a comparison of both profiles considering a set of variables related to consumption, clinical severity and subjective effects experienced. From a cross-sectional design, 173 adolescents (104 men and 69 women) aged 13 to 18 asking for treatment for cannabis use disorder in an Addictive Behavior Unit (UCAD) from the hospital were recruited. For the assessment, an ad hoc protocol was employed to register consumption, the Millon Adolescent Clinical Inventory (MACI) and the Addiction Research Center Inventory (ARCI) 49-item short form were also administered. Factor analysis suggested a two-profile solution: Introverted, Inhibited, Doleful, Dramatizing (-), Egotistic (-), Self-demeaning and Borderline tendency scales composed the internalizing profile, and Submissive (-), Unruly, Forceful, Conforming (-) and Oppositional scales composed the externalizing profile. The comparative analysis showed that the internalizing profile has higher levels of clinical severity and more subjective effects reported than the externalizing profile. These results suggest the need to design specific intervention strategies for each profile

Virtual Reality-Based Early Neurocognitive Stimulation in Critically Ill Patients : A Pilot Randomized Clinical Trial

This study focuses on the application of a non-immersive virtual reality (VR)-based neurocognitive intervention in critically ill patients. Our aim was to assess the feasibility of direct outcome measures to detect the impact of this digital therapy on patients' cognitive and emotional outcomes. Seventy-two mechanically ventilated adult patients were randomly assigned to the "treatment as usual" (TAU, n = 38) or the "early neurocognitive stimulation" (ENRIC, n = 34) groups. All patients received standard intensive care unit (ICU) care. Patients in the ENRIC group also received adjuvant neurocognitive stimulation during the ICU stay. Outcome measures were a full neuropsychological battery and two mental health questionnaires. A total of 42 patients (21 ENRIC) completed assessment one month after ICU discharge, and 24 (10 ENRIC) one year later. At one-month follow-up, ENRIC patients had better working memory scores (p = 0.009, d = 0.363) and showed up to 50% less non-specific anxiety (11.8% vs. 21.1%) and depression (5.9% vs. 10.5%) than TAU patients. A general linear model of repeated measures reported a main effect of group, but not of time or group-time interaction, on working memory, with ENRIC patients outperforming TAU patients (p = 0.008, η 2 = 0.282). Our results suggest that non-immersive VR-based neurocognitive stimulation may help improve short-term working memory outcomes in survivors of critical illness. Moreover, this advantage could be maintained in the long term. An efficacy trial in a larger sample of participants is feasible and must be conducted

Patient-ventilator asynchronies during mechanical ventilation : current knowledge and research priorities

Mechanical ventilation is common in critically ill patients. This life-saving treatment can cause complications and is also associated with long-term sequelae. Patient-ventilator asynchronies are frequent but underdiagnosed, and they have been associated with worse outcomes. Asynchronies occur when ventilator assistance does not match the patient's demand. Ventilatory overassistance or underassistance translates to different types of asynchronies with different effects on patients. Underassistance can result in an excessive load on respiratory muscles, air hunger, or lung injury due to excessive tidal volumes. Overassistance can result in lower patient inspiratory drive and can lead to reverse triggering, which can also worsen lung injury. Identifying the type of asynchrony and its causes is crucial for effective treatment. Mechanical ventilation and asynchronies can affect hemodynamics. An increase in intrathoracic pressure during ventilation modifies ventricular preload and afterload of ventricles, thereby affecting cardiac output and hemodynamic status. Ineffective efforts can decrease intrathoracic pressure, but double cycling can increase it. Thus, asynchronies can lower the predictive accuracy of some hemodynamic parameters of fluid responsiveness. New research is also exploring the psychological effects of asynchronies. Anxiety and depression are common in survivors of critical illness long after discharge. Patients on mechanical ventilation feel anxiety, fear, agony, and insecurity, which can worsen in the presence of asynchronies. Asynchronies have been associated with worse overall prognosis, but the direct causal relation between poor patient-ventilator interaction and worse outcomes has yet to be clearly demonstrated. Critical care patients generate huge volumes of data that are vastly underexploited. New monitoring systems can analyze waveforms together with other inputs, helping us to detect, analyze, and even predict asynchronies. Big data approaches promise to help us understand asynchronies better and improve their diagnosis and management. Although our understanding of asynchronies has increased in recent years, many questions remain to be answered. Evolving concepts in asynchronies, lung crosstalk with other organs, and the difficulties of data management make more efforts necessary in this field

Development and validation of a sample entropy-based method to identify complex patient-ventilator interactions during mechanical ventilation

Patient-ventilator asynchronies can be detected by close monitoring of ventilator screens by clinicians or through automated algorithms. However, detecting complex patient-ventilator interactions (CP-VI), consisting of changes in the respiratory rate and/or clusters of asynchronies, is a challenge. Sample Entropy (SE) of airway flow (SE-Flow) and airway pressure (SE-Paw) waveforms obtained from 27 critically ill patients was used to develop and validate an automated algorithm for detecting CP-VI. The algorithm’s performance was compared versus the gold standard (the ventilator’s waveform recordings for CP-VI were scored visually by three experts; Fleiss’ kappa = 0.90 (0.87–0.93)). A repeated holdout cross-validation procedure using the Matthews correlation coefficient (MCC) as a measure of effectiveness was used for optimization of different combinations of SE settings (embedding dimension, m, and tolerance value, r), derived SE features (mean and maximum values), and the thresholds of change (Th) from patient’s own baseline SE value. The most accurate results were obtained using the maximum values of SE-Flow (m = 2, r = 0.2, Th = 25%) and SE-Paw (m = 4, r = 0.2, Th = 30%) which report MCCs of 0.85 (0.78–0.86) and 0.78 (0.78–0.85), and accuracies of 0.93 (0.89–0.93) and 0.89 (0.89–0.93), respectively. This approach promises an improvement in the accurate detection of CP-VI, and future study of their clinical implications.This work was funded by projects PI16/01606, integrated in the Plan Nacional de R+D+I and co-funded by the ISCIII- Subdirección General de Evaluación y el Fondo Europeo de Desarrollo Regional (FEDER). RTC-2017-6193-1 (AEI/FEDER UE). CIBER Enfermedades Respiratorias, and Fundació Parc Taulí

Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation

The ideal moment to withdraw respiratory supply of patients under Mechanical Ventilation at Intensive Care Units (ICU), is not easy to be determined for clinicians. Although the Spontaneous Breathing Trial (SBT) provides a measure of the patients’ readiness, there is still around 15–20% of predictive failure rate. This work is a proof of concept focused on adding new value to the prediction of the weaning outcome. Heart Rate Variability (HRV) and Cardiopulmonary Coupling (CPC) methods are evaluated as new complementary estimates to assess weaning readiness. The CPC is related to how the mechanisms regulating respiration and cardiac pumping are working simultaneously, and it is defined from HRV in combination with respiratory information. Three different techniques are used to estimate the CPC, including Time-Frequency Coherence, Dynamic Mutual Information and Orthogonal Subspace Projections. The cohort study includes 22 patients in pressure support ventilation, ready to undergo the SBT, analysed in the 24 h previous to the SBT. Of these, 13 had a successful weaning and 9 failed the SBT or needed reintubation –being both considered as failed weaning. Results illustrate that traditional variables such as heart rate, respiratory frequency, and the parameters derived from HRV do not differ in patients with successful or failed weaning. Results revealed that HRV parameters can vary considerably depending on the time at which they are measured. This fact could be attributed to circadian rhythms, having a strong influence on HRV values. On the contrary, significant statistical differences are found in the proposed CPC parameters when comparing the values of the two groups, and throughout the whole recordings. In addition, differences are greater at night, probably because patients with failed weaning might be experiencing more respiratory episodes, e.g. apneas during the night, which is directly related to a reduced respiratory sinus arrhythmia. Therefore, results suggest that the traditional measures could be used in combination with the proposed CPC biomarkers to improve weaning readiness

Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation

The ideal moment to withdraw respiratory supply of patients under Mechanical Ventilation at Intensive Care Units (ICU), is not easy to be determined for clinicians. Although the Spontaneous Breathing Trial (SBT) provides a measure of the patients' readiness, there is still around 15-20% of predictive failure rate. This work is a proof of concept focused on adding new value to the prediction of the weaning outcome. Heart Rate Variability (HRV) and Cardiopulmonary Coupling (CPC) methods are evaluated as new complementary estimates to assess weaning readiness. The CPC is related to how the mechanisms regulating respiration and cardiac pumping are working simultaneously, and it is defined from HRV in combination with respiratory information. Three different techniques are used to estimate the CPC, including Time-Frequency Coherence, Dynamic Mutual Information and Orthogonal Subspace Projections. The cohort study includes 22 patients in pressure support ventilation, ready to undergo the SBT, analysed in the 24 h previous to the SBT. Of these, 13 had a successful weaning and 9 failed the SBT or needed reintubation -being both considered as failed weaning. Results illustrate that traditional variables such as heart rate, respiratory frequency, and the parameters derived from HRV do not differ in patients with successful or failed weaning. Results revealed that HRV parameters can vary considerably depending on the time at which they are measured. This fact could be attributed to circadian rhythms, having a strong influence on HRV values. On the contrary, significant statistical differences are found in the proposed CPC parameters when comparing the values of the two groups, and throughout the whole recordings. In addition, differences are greater at night, probably because patients with failed weaning might be experiencing more respiratory episodes, e.g. apneas during the night, which is directly related to a reduced respiratory sinus arrhythmia. Therefore, results suggest that the traditional measures could be used in combination with the proposed CPC biomarkers to improve weaning readiness

The impact of Mn nonstoichiometry on the oxygen mass transport properties of La0.8Sr0.2MnyO3±δ thin films

Oxygen mass transport in perovskite oxides is relevant for a variety of energy and information technologies. In oxide thin films, cation nonstoichiometry is often found but its impact on the oxygen transport properties is not well understood. Here, we used oxygen isotope exchange depth profile technique coupled with secondary ion mass spectrometry to study oxygen mass transport and the defect compensation mechanism of Mn-deficient La0.8Sr0.2Mn (y) O-3 +/-delta epitaxial thin films. Oxygen diffusivity and surface exchange coefficients were observed to be consistent with literature measurements and to be independent on the degree of Mn deficiency in the layers. Defect chemistry modeling, together with a collection of different experimental techniques, suggests that the Mn-deficiency is mainly compensated by the formation of La-x(Mn) antisite defects. The results highlight the importance of antisite defects in perovskite thin films for mitigating cationic nonstoichiometry effects on oxygen mass transport properties