Patient Perspectives on AI-Driven Predictions of Schizophrenia Relapses: Understanding Concerns and Opportunities for Self-Care and Treatment.

Early detection and intervention for relapse is important in the treatment of schizophrenia spectrum disorders. Researchers have developed AI models to predict relapse from patient-contributed data like social media. However, these models face challenges, including misalignment with practice and ethical issues related to transparency, accountability, and potential harm.

Cross-Platform Detection of Psychiatric Hospitalization via Social Media Data: Comparison Study.

Background: Previous research has shown the feasibility of using machine learning models trained on social media data from a single platform (eg, Facebook or Twitter) to distinguish individuals either with a diagnosis of mental illness or experiencing an adverse outcome from healthy controls. However, the performance of such models on data from novel social media platforms unseen in the training data (eg, Instagram and TikTok) has not been investigated in previous literature.

Objective: Our study examined the feasibility of building machine learning classifiers that can effectively predict an upcoming psychiatric hospitalization given social media data from platforms unseen in the classifiers' training data despite the preliminary evidence on identity fragmentation on the investigated social media platforms.

Understanding the COVID-19 Infodemic: Analyzing User-Generated Online Information During a COVID-19 Outbreak in Vietnam.

Objectives: Online misinformation has reached unprecedented levels during the coronavirus disease 2019 (COVID-19) pandemic. This study analyzed the magnitude and sentiment dynamics of misinformation and unverified information about public health interventions during a COVID-19 outbreak in Da Nang, Vietnam, between July and September 2020.

Methods: We analyzed user-generated online information about five public health interventions during the Da Nang outbreak.

Using 'infodemics' to understand public awareness and perception of SARS-CoV-2: A longitudinal analysis of online information about COVID-19 incidence and mortality during a major outbreak in Vietnam, July-September 2020.

Background: Trends in the public perception and awareness of COVID-19 over time are poorly understood. We conducted a longitudinal study to analyze characteristics and trends of online information during a major COVID-19 outbreak in Da Nang province, Vietnam in July-August 2020 to understand public awareness and perceptions during an epidemic.

Methods: We collected online information on COVID-19 incidence and mortality from online platforms in Vietnam between 1 July and 15 September, 2020, and assessed their trends over time against the epidemic curve.

Bioactive chemical constituents, in vitro anti-proliferative activity and in vivo toxicity of the extract of Curcuma singularis Gagnep rhizomes.

Ethnopharmacological Relevance: Curcuma singularis Gagnep is a Vietnamese medicinal plant which has been commonly used as a medicinal remedy in traditional and folk medicines for improving health as well as for treating some diseases, like rheumatoid arthritis, kidney failure. However, pharmacological effects, including anti-cancer activity and the safety of this plant has not been fully investigated.

Aim Of The Study: This study aimed to investigate the in vitro anti-growth activity of an extract derived from Curcuma singularis rhizome extract (CSE) against cell lines as well as determine its phytochemical composition.

Committee machine that votes for similarity between materials.

A method has been developed to measure the similarity between materials, focusing on specific physical properties. The information obtained can be utilized to understand the underlying mechanisms and support the prediction of the physical properties of materials. The method consists of three steps: variable evaluation based on nonlinear regression, regression-based clustering, and similarity measurement with a committee machine constructed from the clustering results.

Localized Charge Transfer in Two-Dimensional Molybdenum Trioxide.

Molybdenum trioxide is an interesting inorganic system in which the empty 4d states have potential to hold extra electrons and therefore can change states from insulating opaque (MoO) to colored semimetallic (HMoO). Here, we characterize the local electrogeneration and charge transfer of the synthetic layered two-dimensional 2D MoO-II (a polymorph of MoO and analogous to α-MoO) in response to two different redox couples, i.e.

Direct Observation of Indium Conductive Filaments in Transparent, Flexible, and Transferable Resistive Switching Memory.

Electronics with multifunctionalities such as transparency, portability, and flexibility are anticipated for future circuitry development. Flexible memory is one of the indispensable elements in a hybrid electronic integrated circuit as the information storage device. Herein, we demonstrate a transparent, flexible, and transferable hexagonal boron nitride (hBN)-based resistive switching memory with indium tin oxide (ITO) and graphene electrodes on soft polydimethylsiloxane (PDMS) substrate.

Coexistence of Write Once Read Many Memory and Memristor in blend of Poly(3,4-ethylenedioxythiophene): polystyrene sulfonate and Polyvinyl Alcohol.

In this work, the coexistence of Write Once Read Many Memory (WORM) and memristor can be achieved in a single device of Poly(3,4-ethylenedioxythiophene): polystyrene sulfonate (PEDOT: PSS) and Polyvinyl Alcohol (PVA) blend organic memory system. In memristor mode, the bistable resistance states of the device can be cycled for more than 1000 times. Once a large negative bias of -8V was applied to the device, it was switched to permanent high resistance state that cannot be restored back to lower resistance states.

Direct Observation of Conducting Filaments in Tungsten Oxide Based Transparent Resistive Switching Memory.

Transparent nonvolatile memory has great potential in integrated transparent electronics. Here, we present highly transparent resistive switching memory using stoichiometric WO film produced by cathodic electrodeposition with indium tin oxide electrodes. The memory device demonstrates good optical transmittance, excellent operative uniformity, low operating voltages (+0.

Resistive Switching Memory Phenomena in PEDOT PSS: Coexistence of Switchable Diode Effect and Write Once Read Many Memory.

We study resistive switching memory phenomena in conducting polymer PEDOT PSS. In the same film, there are two types of memory behavior coexisting; namely, the switchable diode effect and write once read many memory. This is the first report on switchable diode phenomenon based on conducting organic materials.

Data mining for materials design: a computational study of single molecule magnet.

We develop a method that combines data mining and first principles calculation to guide the designing of distorted cubane Mn(4+)Mn3(3+) single molecule magnets. The essential idea of the method is a process consisting of sparse regressions and cross-validation for analyzing calculated data of the materials. The method allows us to demonstrate that the exchange coupling between Mn(4+) and Mn(3+) ions can be predicted from the electronegativities of constituent ligands and the structural features of the molecule by a linear regression model with high accuracy.

Program impact evaluation using a matching method with panel data.

Difference-in-differences with matching is a popular method to measure the impact of an intervention in health and social sciences. This method requires baseline data, that is, data before interventions, which are not always available in reality. Instead, panel data with two time periods are often collected after interventions begin.

Total transmission and total reflection by zero index metamaterials with defects.

We theoretically investigate microwave transmission through a zero-index metamaterial loaded with dielectric defects. The metamaterial is impedance matched to free space, with the permittivity and permeability tending towards zero over a given frequency range. By simply varying the radii and permittivities of the defects, total transmission or reflection of the impinging electromagnetic wave can be achieved.

A data base for polymer chromatography: dependence of interaction parameters on mobile phase composition.

In chromatography of polymers, retention is determined by the characteristic volumes of the column (pore volume and interstitial volume), the pore diameter, and the interaction parameter. While the influence of the pore diameter is predominant in size exclusion chromatography, the key parameters in liquid adsorption chromatography are the interaction parameter and the pore surface of the column. It is shown, that the retention behaviour of polymers in liquid adsorption chromatography (LAC) can be predicted very well using the accessible volume and pore surface of the column, which can be determined very easily, and the interaction parameters from a data base.