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Core-only InAs nanowires (NWs) remain of continuing interest for application in modern optical and electrical devices. In this paper, we utilize the II-VI semiconductor CdSe as a shell for III-V InAs NWs to protect the electron transport channel in the InAs core from surface effects. This unique material configuration offers both a small lattice mismatch between InAs and CdSe and a pronounced electronic confinement in the core with type-I band alignment at the interface between both materials. Under optimized growth conditions, a smooth interface between the core and shell is obtained. Atom probe tomography (APT) measurements confirm substantial diffusion of In into the shell, forming a remote n-type doping of CdSe. Moreover, field-effect transistors (FETs) are fabricated, and the electron transport characteristics in these devices is investigated. Finally, band structure simulations are performed and confirm the presence of an electron transport channel in the InAs core that, at higher gate voltages, extends into the CdSe shell region. These results provide a promising basis toward the application of hybrid III-V/II-VI core/shell nanowires in modern electronics.

Psychotherapy can be improved by integrating the study of mediators (how it works) and moderators (for whom it works). To demonstrate this integration, we studied the relationship between resource activation, problem-coping experiences and symptoms in cognitive-behavior therapy (CBT) for depression, to obtain preliminary insights on causal inference (which process leads to symptom improvement?) and prediction (which one for whom?)., A sample of 715 patients with depression who received CBT was analyzed. Hierarchical Bayesian continuous time dynamic modeling was used to study the temporal dynamics between the variables analyzed within the first ten sessions. Depression and self-efficacy at baseline were examined as predictors of these dynamics., There were significant cross-effects between the processes studied. Under typical assumptions, resource activation had a significant effect on symptom improvement. Problem-coping experience had a significant effect on resource activation. Depression and self-efficacy moderated these effects. However, when system noise was considered, these effects may be affected by other processes., Resource activation was strongly associated with symptom improvement. To the extent of inferring causality, for patients with mild-moderate depression and high self-efficacy, promoting resource activation can be recommended. For patients with severe depression and low self-efficacy, promoting problem-coping experiences can be recommended.

Objective: The occurrence of dropout from psychological interventions is associated with poor treatment outcome and high health, societal and economic costs. Recently, machine learning (ML) algorithms have been tested in psychotherapy outcome research. Dropout predictions are usually limited by imbalanced datasets and the size of the sample. This paper aims to improve dropout prediction by comparing ML algorithms, sample sizes and resampling methods. Method: Twenty ML algorithms were examined in twelve subsamples (drawn from a sample of N  = 49,602) using four resampling methods in comparison to the absence of resampling and to each other. Prediction accuracy was evaluated in an independent holdout dataset using the F 1 -Measure. Results: Resampling methods improved the performance of ML algorithms and down-sampling can be recommended, as it was the fastest method and as accurate as the other methods. For the highest mean F 1 -Score of .51 a minimum sample size of N  = 300 was necessary. No specific algorithm or algorithm group can be recommended. Conclusion: Resampling methods could improve the accuracy of predicting dropout in psychological interventions. Down-sampling is recommended as it is the least computationally taxing method. The training sample should contain at least 300 cases.

Isolated impurity states in epitaxially grown semiconductor systems possess important radiative features such as distinct wavelength emission with a very short radiative lifetime and low inhomogeneous broadening, which make them promising for the generation of indistinguishable single photons. In this study, we investigate chlorine-doped ZnSe/ZnMgSe quantum well (QW) nanopillar (NP) structures as a highly efficient solid-state single-photon source operating at cryogenic temperatures. We show that single photons are generated due to the radiative recombination of excitons bound to neutral Cl atoms in ZnSe QW and the energy of the emitted photon can be tuned from about 2.85 down to 2.82 eV with ZnSe well width increase from 2.7 to 4.7 nm. Following the developed advanced technology, we fabricate NPs with a diameter of about 250 nm using a combination of dry and wet-chemical etching of epitaxially grown ZnSe/ZnMgSe QW structures. The remaining resist mask serves as a spherical- or cylindrical-shaped solid immersion lens on top of NPs and leads to the emission intensity enhancement by up to an order of magnitude in comparison to the pillars without any lenses. NPs with spherical-shaped lenses show the highest emission intensity values. The clear photon-antibunching effect is confirmed by the measured value of the second-order correlation function at a zero time delay of 0.14. The developed single-photon sources are suitable for integration into scalable photonic circuits.

The integration of semiconductor Josephson junctions (JJs) in superconducting quantum circuits provides a versatile platform for hybrid qubits and offers a powerful way to probe exotic quasiparticle excitations. Recent proposals for using circuit quantum electrodynamics (cQED) to detect topological superconductivity motivate the integration of novel topological materials in such circuits. Here, we report on the realization of superconducting transmon qubits implemented with (Bi 0.06 Sb 0.94 ) 2 Te 3 topological insulator (TI) JJs using ultrahigh vacuum fabrication techniques. Microwave losses on our substrates, which host monolithically integrated hardmasks used for the selective area growth of TI nanostructures, imply microsecond limits to relaxation times and, thus, their compatibility with strong-coupling cQED. We use the cavity-qubit interaction to show that the Josephson energy of TI-based transmons scales with their JJ dimensions and demonstrate qubit control as well as temporal quantum coherence. Our results pave the way for advanced investigations of topological materials in both novel Josephson and topological qubits.

Background: Changes during psychotherapy often include sudden symptom improvements, called sudden gains (SGs), which have been identified as being superior to gradual symptom change with regard to treatment success. This study investigates the role of therapists in initiating and/or consolidating SGs., Methods: The analyses are based on a sample of patients ( N  = 1937) who were seen by 155 therapists and received individual psychotherapy at a university outpatient clinic. First, the therapist effect (TE) on SG was investigated using multilevel modeling (MLM). Second, MLM was used to explore the relative importance of patient and therapist variability in SGs as they relate to outcome., Results: The TE on SGs accounted for 1.8% of variance, meaning that therapists are accountable for inter-individual differences in their patients' likelihood to experience SGs. Furthermore, results revealed a significant effect of SGs on outcome for both levels, while therapist differences regarding the consolidation of SGs were not significant., Conclusions: The analyses indicated that some therapists are better in facilitating and initiating SGs. The process of triggering SGs seems to be a therapist skill or competence, which opens up an additional pathway to positive outcomes that could be used to improve clinical training.

Background: About 30% of patients drop out of cognitive-behavioural therapy (CBT), which has implications for psychiatric and psychological treatment. Findings concerning drop out remain heterogeneous., Aims: This paper aims to compare different machine-learning algorithms using nested cross-validation, evaluate their benefit in naturalistic settings, and identify the best model as well as the most important variables., Method: The data-set consisted of 2543 out-patients treated with CBT. Assessment took place before session one. Twenty-one algorithms and ensembles were compared. Two parameters (Brier score, area under the curve (AUC)) were used for evaluation., Results: The best model was an ensemble that used Random Forest and nearest-neighbour modelling. During the training process, it was significantly better than generalised linear modelling (GLM) (Brier score: d = -2.93, 95% CI (-3.95, -1.90)); AUC: d = 0.59, 95% CI (0.11 to 1.06)). In the holdout sample, the ensemble was able to correctly identify 63.4% of cases of patients, whereas the GLM only identified 46.2% correctly. The most important predictors were lower education, lower scores on the Personality Style and Disorder Inventory (PSSI) compulsive scale, younger age, higher scores on the PSSI negativistic and PSSI antisocial scale as well as on the Brief Symptom Inventory (BSI) additional scale (mean of the four additional items) and BSI overall scale., Conclusions: Machine learning improves drop-out predictions. However, not all algorithms are suited to naturalistic data-sets and binary events. Tree-based and boosted algorithms including a variable selection process seem well-suited, whereas more advanced algorithms such as neural networks do not.

Objective: Thus far, most applications in precision mental health have not been evaluated prospectively. This article presents the results of a prospective randomized-controlled trial investigating the effects of a digital decision support and feedback system, which includes two components of patient-specific recommendations: (a) a clinical strategy recommendation and (b) adaptive recommendations for patients at risk for treatment failure., Method: Therapist-patient dyads ( N = 538) in a cognitive behavioral therapy outpatient clinic were randomized to either having access to a decision support system (intervention group; n = 335) or not (treatment as usual; n = 203). First, treatment strategy recommendations (problem-solving, motivation-oriented, or a mix of both strategies) for the first 10 sessions were evaluated. Second, the effect of psychometric feedback enhanced with clinical problem-solving tools on treatment outcome was investigated., Results: The prospective evaluation showed a differential effect size of about 0.3 when therapists followed the recommended treatment strategy in the first 10 sessions. Moreover, the linear mixed models revealed therapist symptom awareness and therapist attitude and confidence as significant predictors of an outcome as well as therapist-rated usefulness of feedback as a significant moderator of the feedback-outcome and the not on track-outcome associations. However, no main effects were found for feedback., Conclusions: The results demonstrate the importance of prospective studies and the high-quality implementation of digital decision support tools in clinical practice. Therapists seem to be able to learn from such systems and incorporate them into their clinical practice to enhance patient outcomes, but only when implementation is successful. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The current study employed machine learning to investigate whether the inclusion of observer-rated therapist interventions and skills in early sessions of psychotherapy improved dropout prediction beyond intake assessments. Patients were treated by postgraduate clinicians at a university outpatient clinic. Psychometric instruments were assessed at intake and therapeutic interventions and skills in the third session were routinely rated by independent observers. After variable preselection, an elastic net algorithm was used to build two dropout prediction models, one including and one excluding observer-rated session variables. The best model included observer-rated variables and was significantly superior to the model including intake variables only. Alongside intake variables, two observer-rated variables significantly predicted dropout: therapist use of feedback and summaries and treatment difficulty. Although not retained in the final prediction model, the observer-rated use of cognitive techniques was also significantly correlated with dropout. Observer ratings of therapist interventions and skills in early sessions of psychotherapy improve predictors of dropout from psychotherapy beyond intake variables alone. Future research could work toward personalizing dropout predictions to the specific dyad, thereby improving their validity and aiding therapists to recognize and react to increased dropout risk., (Copyright © 2021. Published by Elsevier Ltd.)

Ethanol exposure and early life stress during brain development are associated with an increased risk of developing psychiatric disorders. We used a third-trimester equivalent model of fetal alcohol spectrum disorders combined with a maternal separation (MS) protocol to evaluate whether these stressors cause sexually dimorphic behavioral and hippocampal dendritic arborization responses in adolescent rats. Wistar rat pups were divided into four experimental groups: 1) Control; 2) MS (MS, for 3 h/day from postnatal (PND) 2 to PND14); 3) EtOH (EtOH, 5 g/kg/day, i.p., PND2, 4, 6, 8, and 10); 4) EtOH + MS. All animals were divided into two cohorts and subjected to a battery of behavioral tests when they reached adolescence (PND37-44). Animals from cohort 1 were submitted to: 1) the open field test; 2) self-cleaning behavior (PND38); and 3) the motivation test (PND39-41). Animals from cohort 2 were submitted to: 1) the novel object recognition (PND37-39); 2) social investigation test (PND40); and 3) Morris water maze test (PND41-44). At PND45, the animals were euthanized, and the brains were collected for subsequent dendritic analysis. Postnatal ethanol exposure (PEE) caused anxiety-like behavior in females and reduced motivation, and increased hippocampal dendritic arborization in both sexes. MS reduced body weight, increased locomotor activity in females, and increased motivation, and hippocampal dendritic arborization in both sexes. We found that males from the EtOH + MS groups are more socially engaged than females, who were more interested in sweets than males. Altogether, these data suggest that early life adverse conditions may alter behavior in a sex-dependent manner in adolescent rats., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Josephson junctions based on InAs semiconducting nanowires and Nb superconducting electrodes are fabricated in situ by a special shadow evaporation scheme for the superconductor electrode. Compared to other metallic superconductors such as Al, Nb has the advantage of a larger superconducting gap which allows operation at higher temperatures and magnetic fields. Our junctions are fabricated by shadow evaporation of Nb on pairs of InAs nanowires grown selectively on two adjacent tilted Si (111) facets and crossing each other at a small distance. The upper wire relative to the deposition source acts as a shadow mask determining the gap of the superconducting electrodes on the lower nanowire. Electron microscopy measurements show that the fully in situ fabrication method gives a clean InAs/Nb interface. A clear Josephson supercurrent is observed in the current-voltage characteristics, which can be controlled by a bottom gate. The large excess current indicates a high junction transparency. Under microwave radiation, pronounced integer Shapiro steps are observed suggesting a sinusoidal current-phase relation. Owing to the large critical field of Nb, the Josephson supercurrent can be maintained to magnetic fields exceeding 1 T. Our results show that in situ prepared Nb/InAs nanowire contacts are very interesting candidates for superconducting quantum circuits requiring large magnetic fields., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

The third wave of cognitive behavioral therapy (CBT) has increased the heterogeneity of today's CBT practice, while developments in patient-focused research are paving the road to the empirical personalization of CBT. This paper presents the development and psychometric properties of a therapy video rating instrument, which was designed to adequately assess the treatment integrity (adherence and competence) of modern, personalized CBT. The Inventory of Therapeutic Interventions and Skills (ITIS) was developed based on two existing CBT adherence and competence scales and augmented with third wave content and overarching therapeutic strategies. The instrument was then applied by graduate students and post-graduate clinicians to rate N = 185 therapy videos from N = 70 patients treated at a university outpatient clinic. Descriptive results, inter-rater reliability, item structure, and associations with session outcome and alliance were examined. Average inter-rater reliability was excellent for Interventions items and good for Skills items. Intercorrelations were low between Interventions items, but higher and significant between Skills items, which loaded on a single factor. Several ITIS items were shown to be predictive of session outcome and alliance, even after controlling for the nested data structure. Implications of these results for future research and clinical training are discussed.

The interplay of Dirac physics and induced superconductivity at the interface of a 3D topological insulator (TI) with an s-wave superconductor (S) provides a new platform for topologically protected quantum computation based on elusive Majorana modes. To employ such S-TI hybrid devices in future topological quantum computation architectures, a process is required that allows for device fabrication under ultrahigh vacuum conditions. Here, we report on the selective area growth of (Bi,Sb) 2 Te 3 TI thin films and stencil lithography of superconductive Nb for a full in situ fabrication of S-TI hybrid devices via molecular-beam epitaxy. A dielectric capping layer was deposited as a final step to protect the delicate surfaces of the S-TI hybrids at ambient conditions. Transport experiments in as-prepared Josephson junctions show highly transparent S-TI interfaces and a missing first Shapiro step, which indicates the presence of Majorana bound states. To move from single junctions towards complex circuitry for future topological quantum computation architectures, we monolithically integrated two aligned hardmasks to the substrate prior to growth. The presented process provides new possibilities to deliberately combine delicate quantum materials in situ at the nanoscale.

We report the in situ growth of crystalline aluminum (Al) and niobium (Nb) shells on indium arsenide (InAs) nanowires. The nanowires are grown on Si(111) substrates by molecular beam epitaxy (MBE) without foreign catalysts in the vapor-solid (VS) mode. The metal shells are deposited by electron-beam evaporation in a metal MBE. High quality superconductor/semiconductor (SC/SM) hybrid structures such as Al/InAs and Nb/InAs are of interest for ongoing research in the fields of gateable Josephson junctions and quantum information related research. Systematic investigations of the deposition parameters suitable for metal shell growth are conducted. In the case of Al, the substrate temperature, the growth rate and the shell thickness are considered. The substrate temperature as well as the angle of the impinging deposition flux are explored for Nb shells. The core-shell hybrid structures are characterized by electron microscopy and X-ray spectroscopy. Our results show that the substrate temperature is a crucial parameter in enabling the deposition of smooth Al layers. Contrarily, Nb films are less dependent on substrate temperature but are strongly affected by the deposition angle. At a temperature of 200 °C Nb reacts with InAs, dissolving the nanowire crystal. Our investigations result in smooth metal shells exhibiting an impurity and defect free, crystalline SC/InAs interface. Additionally, we find that the SC crystal structure is not affected by stacking faults present in the InAs nanowires.