Exploring the Design Space of Mobile Applications for Addressing Depression-associated Autobiographical Memory Impairments

Depression is an affective disorder with a range of cognitive biases and distortions, which drives depression onset, development and maintenance. This PhD research aims to support end users with non-clinical depression, by exploring the possibility of mitigating a range of depression-associated impairments in autobiographical memory processing (D-ABMs) through mobile applications. Emerging psychological interventions targeting these disrupted D-ABMs issues hold enormous potential of mitigating depression symptoms and thus been widely explored in the field of psychology. However, they have received less support from HCI research in depression . Current HCI work on digital interventions mainly support the digitization of mainstream psychological interventions such as Cognitive Behavioural Therapy (CBT) as it is acknowledged as the most evidence-based interventions, and its pre-structured nature makes it easier to be transferred into digital app design. However, the pre-defined nature of CBT related interventions can also bring various limitations. Different to the pre-structured interventions such as CBT, D-ABMs interventions hold promises in bringing more person-centric training content that are more flexible to app users’ needs. This thesis aims to explore the design space of mobile apps for D-ABMs. For this purpose, first, I explored the key effective components in current depression interventions while addressing D-ABMs, and analysed how they can inform the design of apps for supporting these interventions. Then, I explored the combination of app features to be included in the design of D-ABM apps, which can support these therapeutic components. Finally, I investigated into an effective design method for helping future designers of D-ABM apps to utilise the empirical findings gained from this thesis work. Overall, this thesis provides empirical exploration and design perspective that demonstrate ways of adapting memory assistive technologies to support the mitigation of depression associated cognitive dysfunctions and consequently alleviating depressive symptoms. The work aims to draw attention to depression-associated cognitive impairments as a less explored space in the filed of HCI, and to inspire HCI researchers to develop novel classes of mobile-based technologies for addressing a wide range of cognitive impairments that are associated depression. The contribution of this thesis opens up new design opportunities for both memory assistive and depression management technologies. The work aims to broaden the awareness of HCI researchers of mental conditions that involve autobiographical memory impairments besides episodic memory loss, such as depression, PTSD, or anxiety, which can be benefited from memory technologies that tailored for each specific conditions

Reviewing and evaluating mobile apps for memory impairments in depression

Depression is a major affective disorder which influences autobiographical memory processing abilities. Mobile phones hold great potential for delivering effective self-help treatments that target depression and for assisting users’ memory processing. This work explores commercial apps that support users’ everyday challenges associated with depression and in particular memory processing. Our results highlight the current functionalities of top-rated apps on major marketplaces, which could be used to inform novel functionalities, better tailored to address depression-related memory issues and consequently reduce users’ depressive symptoms

Metal Injection Moulding of High Nb-Containing TiAl Alloy and Its Oxidation Behaviour at 900°C

High Nb-containing TiAl alloy with a nominal composition of Ti-45Al-8.5Nb-0.2W-0.2B-0.02Y (at %) was fabricated by metal injection moulding (MIM) technology with an improved wax-based binder. The critical powder loading and feedstock rheological behaviour were determined. The influence of sintering temperature on microstructures and mechanical properties of the sintered samples and their oxidation behaviour were also investigated. Results showed that a feedstock, with a powder loading of 68 vol % and good flowability, could be obtained by using the improved binder, and oxygen pick-up was lower than that of the sample prepared by using a traditional binder. The ultimate tensile strength (UTS) and plastic elongation of the sample sintered at 1480 °C for 2 h were 412 MPa and 0.33%, at room temperature, respectively. The 1480 °C-sintered sample consisted of γ/α2 lamellar microstructure with the average colony size of about 70 µm, and its porosity was about 4%. The sintered alloy showed better oxidation resistance than that of the cast alloy counterpart

Functionality of Top-Rated Mobile Apps for Depression:Systematic Search and Evaluation

Background: In the last decade, there has been a proliferation of mobile apps claiming to support the needs of people living with depression. However, it is unclear what functionality apps for depression actually provide and for whom they are intended. Objective: This paper aims to explore the key features of top-rated apps for depression, including descriptive characteristics, functionality, and ethical concerns in order to support better-informed design of apps for depression. Methods: We reviewed top-rated iOS and Android mobile apps for depression retrieved from app marketplaces in spring 2019. We applied a systematic analysis to review the selected apps, for which data was gathered from the two marketplaces, and through direct use of the apps. We report an in-depth analysis of app functionality, namely: screening, tracking, and provision of interventions. Of the initially identified 482 apps, 29 apps met the criteria for inclusion in this review. Apps were included if they remained accessible at the moment of evaluation, were offered in mental health relevant categories, received a review score greater than 4.0 out of 5.0 contributed by more than 100 reviewers, and have depression as a primary target. Results: The analysis revealed that a majority of apps specify the evidence-base for their intervention (62%, 18/29) while a smaller proportion describe receiving clinical input into their design (41%, 12/29). All selected apps are rated as suitable for children and adolescents on the marketplace, but 83% (24/29) do not provide a privacy policy consistent with their rating. Findings also show that most apps provide multiple functions. The most commonly implemented functions include provision of interventions (83%, 24/29) either as digitalized therapeutic intervention or as support for mood expression, tracking (66%, 19/29) of moods, thoughts or behaviors for supporting the intervention, and screening (31%, 9/29) to inform the decision to use the app and its intervention. Some apps include overtly negative content. Conclusions: Currently available top-ranked apps for depression on the major marketplaces provide diverse functionality to benefit users across a range of age groups, however guidelines and frameworks are still needed to ensure users’ privacy and safety while using them. Suggestions include clearly defining the age of the target population and explicit disclosure of the sharing of users’ sensitive data with third parties. Additionally, we found an opportunity for apps to better leverage digital affordances for mitigating harm, for personalizing interventions, and for tracking multimodal content. The study further demonstrates the need to consider potential risks while using depression apps, including the use of non-validated screening tools, tracking negative moods or thinking patterns, and exposing users to negative emotional expression content

Insight-HXMT observations of Swift J0243.6+6124 during its 2017-2018 outburst

The recently discovered neutron star transient Swift J0243.6+6124 has been monitored by {\it the Hard X-ray Modulation Telescope} ({\it Insight-\rm HXMT). Based on the obtained data, we investigate the broadband spectrum of the source throughout the outburst. We estimate the broadband flux of the source and search for possible cyclotron line in the broadband spectrum. No evidence of line-like features is, however, found up to $\rm 150~keV$. In the absence of any cyclotron line in its energy spectrum, we estimate the magnetic field of the source based on the observed spin evolution of the neutron star by applying two accretion torque models. In both cases, we get consistent results with $B\rm \sim 10^{13}~G$, $D\rm \sim 6~kpc$ and peak luminosity of $\rm >10^{39}~erg~s^{-1}$ which makes the source the first Galactic ultraluminous X-ray source hosting a neutron star.Comment: publishe

Overview to the Hard X-ray Modulation Telescope (Insight-HXMT) Satellite

As China's first X-ray astronomical satellite, the Hard X-ray Modulation Telescope (HXMT), which was dubbed as Insight-HXMT after the launch on June 15, 2017, is a wide-band (1-250 keV) slat-collimator-based X-ray astronomy satellite with the capability of all-sky monitoring in 0.2-3 MeV. It was designed to perform pointing, scanning and gamma-ray burst (GRB) observations and, based on the Direct Demodulation Method (DDM), the image of the scanned sky region can be reconstructed. Here we give an overview of the mission and its progresses, including payload, core sciences, ground calibration/facility, ground segment, data archive, software, in-orbit performance, calibration, background model, observations and some preliminary results.Comment: 29 pages, 40 figures, 6 tables, to appear in Sci. China-Phys. Mech. Astron. arXiv admin note: text overlap with arXiv:1910.0443

Competition, Division and Unity : The Impact of Market Structures on Trading Quality

The financial market operates as an ecosystem, involving diverse yet interconnected marketplaces and participants. Market design, intricately interacting with technology, regulation, and competition, shapes how participants adapt their trading behavior and therefore influences market performance. This dissertation investigates how market microstructure impacts the behavior of fast and slow traders, the incentive for liquidity provision and liquidity demand, and the competition between exchanges for gaining order flow. Article I examines a strategic solution to the concern that fast arbitrageurs make liquidity provision more costly by picking off quotes before market makers have time to revise them. The solution in question was to prohibit proprietary traders from engaging in liquidity taking, which prevents fast arbitrageurs from sniping market makers’ stale quotes. The results reveal that the trading ban mitigated adverse selection costs and narrowed the bid-ask spread. Market makers experienced higher profits and quoted higher volumes at better prices. The ban successfully eliminated over half of cross-exchange toxic arbitrage trades. Article II evaluates the market quality effects of market fragmentation. The study leverages a quasi-natural experiment, which occurred when the Swiss stock markets suddenly transitioned from fragmentation to centralization in July 2019, following the breakdown of EU-Switzerland equivalence rules. Because this event was unrelated to technological developments, and did not disrupt trading, it establishes a firm ground for identifying the effect of fragmentation. The key finding is that greater market fragmentation improves market liquidity, as captured by bid-ask spreads and depth, while it does not impact market efficiency. These results align with theoretical predictions stating that market fragmentation improves liquidity through quote competition across exchanges. Article III studies the role of restrictions on the minimum tick size and the minimum lot size for determining transaction costs at the futures market. The arrangement of minimum tick and lot sizes by regulators constrains trading at discrete prices and quantities. The study demonstrates, both theoretically and empirically, a trade-off between the restrictions of discrete price and discrete quantity. Given this tradeoff, a futures exchange can minimize futures transaction costs by choosing the optimal futures price. That is, when the futures price is high, it is also relatively more continuous, and the futures quantity is relatively more discrete, compared to the case when the futures price is low. In other words, when the futures price is high rather than low, the lot size restriction causes relatively more friction than the tick size restriction and vice versa. The empirical results strongly support the model.