What Symptoms and How Long? An Interpretable AI Approach for Depression Detection in Social Media

Depression is the most prevalent and serious mental illness, which induces grave financial and societal ramifications. Depression detection is key for early intervention to mitigate those consequences. Such a high-stake decision inherently necessitates interpretability. Although a few depression detection studies attempt to explain the decision based on the importance score or attention weights, these explanations misalign with the clinical depression diagnosis criterion that is based on depressive symptoms. To fill this gap, we follow the computational design science paradigm to develop a novel Multi-Scale Temporal Prototype Network (MSTPNet). MSTPNet innovatively detects and interprets depressive symptoms as well as how long they last. Extensive empirical analyses using a large-scale dataset show that MSTPNet outperforms state-of-the-art depression detection methods with an F1-score of 0.851. This result also reveals new symptoms that are unnoted in the survey approach, such as sharing admiration for a different life. We further conduct a user study to demonstrate its superiority over the benchmarks in interpretability. This study contributes to IS literature with a novel interpretable deep learning model for depression detection in social media. In practice, our proposed method can be implemented in social media platforms to provide personalized online resources for detected depressed patients.Comment: 56 pages, 10 figures, 21 table

What Symptoms and How Long? An Interpretable AI Approach for Depression Detection in Social Media

Depression is the most prevalent and serious mental illness, which induces grave financial and societal ramifications. Depression detection is key for early intervention to mitigate those consequences. Such a high-stake decision inherently necessitates interpretability. Although a few depression detection studies attempt to explain the decision, these explanations misalign with the clinical depression diagnosis criterion that is based on depressive symptoms. To fill this gap, we develop a novel Multi-Scale Temporal Prototype Network (MSTPNet). MSTPNet innovatively detects and interprets depressive symptoms as well as how long they last. Extensive empirical analyses show that MSTPNet outperforms state-of-the-art depression detection methods. This result also reveals new symptoms that are unnoted in the survey approach. We further conduct a user study to demonstrate its superiority over the benchmarks in interpretability. This study contributes to IS literature with a novel interpretable deep learning model for depression detection in social media

A novel iterative approach for mapping local singularities from geochemical data

International audienceThere are many phenomena in nature, such as earthquakes, landslides, floods, and large-scale mineralization that are characterized by singular functions exhibiting scale invariant properties. A local singularity analysis based on multifractal modeling was developed for detection of local anomalies for mineral exploration. An iterative approach is proposed in the current paper for improvement of parameter estimations involved in the local singularity analysis. The advantage of this new approach is demonstrated with de Wijs's zinc data from a sphalerite-quartz vein near Pulacayo in Bolivia. The semivariogram method was used to illustrate the differences between the raw data and the estimated data by the new algorithm. It has been shown that the outcome of the local singularity analysis consists of two components: singularity component characterized by local singularity index and the non-singular component by prefractal parameter

Hybrid Topological Superconductivity and Hinge Majorana Flat Band in Type-II Dirac Semimetals

Type-II Dirac semimetals (DSMs) have a distinct Fermi surface topology, which allows them to host novel topological superconductivity (TSC) different from type-I DSMs. Depending on the relationship between intra- and inter-orbital electron-electron interactions, the phase diagram of superconductivity is obtained in type-II DSMs. We find that when the inter-orbital attraction is dominant, an unconventional inter-orbital intra-spin superconducting (SC) state ($B_{1u}$ and $B_{2u}$ pairing channels of $D_{4h}$ point group) is realized, yielding hybrid TSC, i.e., first- and second-order TSC exists at the same time. Further analysis reveals the Majorana flat bands on the $z$-directed hinges, which penetrate through the whole hinge Brillouin zone and link the projections of the surface helical Majorana cones at time-reversal-invariant momenta. These higher-order hinge modes are symmetry-protected and can even host strong stability against finite $C_{4z}$ rotation symmetry-breaking order. We suggest that experimental realization of these findings can be explored in transition metal dichalcogenides

A meta-analysis of phosphate binders lanthanum carbonate versus sevelamer hydrochloride in patients with end-stage renal disease undergoing hemodialysis

Background and Objectives: The purpose of this study was to compare the effects of phosphate binders lanthanum carbonate (LC) versus sevelamer hydrochloride (SH) in end-stage renal disease (ESRD) patients undergoing hemodialysis.Methods: Studies including randomized controlled trials (RCTs) comparing phosphate binders lanthanum carbonate versus sevelamer hydrochloride, in ESRD patients undergoing hemodialysis, were identified using a pre-defined search strategy. Phosphate, calcium, calcium-phosphorus product, intact parathyroid hormone, alkaline phosphatase, total cholesterol, and triglyceride were extracted and compared by RevMan 5.1 (The Cochrane Collaboration, Oxford, UK).Results: Six studies were identified. Meta-analysis showed that SH treatment reduced levels of phosphate, intact parathyroid hormone, and total serum alkaline phosphatase (ALP) when compared with LC treatment. Furthermore, patients on SH treatment tended to have reduced calcium levels, calcium-phosphorus product, total cholesterol, and triglyceride when compared to patients treated with LC, but there was no statistical difference.Conclusion: SH treatment of patients with ESRD is more effective compared to LC treatment. However, more well-designed random control trails are required for confirmation.Keywords: End-stage renal disease, hemodialysis, phosphate binders, lanthanum carbonate (LC), sevelamer hydrochloride (SH), meta-analysis

Application of local singularity in prospecting potential oil/gas Targets

International audienceTogether with generalized self-similarity and the fractal spectrum, local singularity analysis has been introduced as one part of the new 3S principle and technique for mineral resource assessment based on multifractal modeling, which has been demonstrated to be useful for anomaly delineation. Local singularity is used in this paper to characterize the property of multifractal distribution patterns of geochemical indexes to delineate potential areas for oil/gas exploration using the advanced GeoDAS GIS technology. Geochemical data of four oil/gas indexes, consisting of acid-extracted methane (SC1), ethane (SC2), propane (SC3), and secondary carbonate (?C), from 9637 soil samples amassed within a large area of 11.2×104 km2 in the Songpan-Aba district, Sichuan Province, southwestern China, were analyzed. By eliminating the interference of geochemical oil/gas data with the method of media-modification and Kriging, the prospecting area defined by the local singularity model is better identified and the results show that the subareas with higher singularity exponents for the four oil/gas indexes are potential targets for oil/gas exploration. These areas in the shape of rings or half-rings are spatially associated with the location of the known producing drilling well in this area. The spatial relationship between the anomalies delineated by oil/gas geochemical data and distribution patterns of local singularity exponents is confirmed by using the stable isotope of ?13C

Two elementary band representation model, Fermi surface nesting, and surface topological superconductivity in AAV3_{3}Sb5_ {5} (A=K, Rb, CsA = \text{K, Rb, Cs})

The recently discovered vanadium-based Kagome metals $A$V$_{3}$Sb$_{5}$ ($A = \text{K, Rb, Cs}$) are of great interest with the interplay of charge density wave (CDW) order, band topology and superconductivity. In this paper, by identifying elementary band representations (EBRs), we construct a two-EBR graphene-Kagome model to capture the two low-energy van-Hove-singularity dispersions and, more importantly, the nontrivial band topology in these Kagome metals. This model consists of $A_g@3g$ (V-$d_{x^2-y^2/z^2}$, Kagome sites) and $A_2''@2d$ EBRs (Sb1-$p_z$, honeycomb sites). We have investigated the Fermi surface instability by calculating the electronic susceptibility $\chi(\mathbf{q})$. Prominent Fermi-surface nesting peaks are obtained at three L points, where the $z$ component of the nesting vector shows intimate relationship with the anticrossing point along M--L. The nesting peaks at L are consistent with the $2\times 2\times 2$ CDW reconstruction in these compounds. In addition, the sublattice-resolved bare susceptibility is calculated and similar sharp peaks are observed at the L points, indicating a strong antiferromagnetic fluctuation. Assuming a bulk $s$-wave superconducting pairing, helical surface states and nontrivial superconducting gap are obtained on the (001) surface. In analogous to FeTe$_{1-x}$Se$_{x}$ superconductor, our results establish another material realization of a stoichiometric superconductor with nontrivial band topology, providing a promising platform for studying exotic Majorana physics in condensed matte

MoTe2: A Type-II Weyl Topological Metal

Based on the ab initio calculations, we show that MoTe2, in its low-temperature orthorhombic structure characterized by an X-ray diffraction study at 100 K, realizes 4 type-II Weyl points between the N-th and N+1-th bands, where N is the total number of valence electrons per unit cell. Other WPs and nodal lines between different other bands also appear close to the Fermi level due to a complex topological band structure. We predict a series of strain-driven topological phase transitions in this compound, opening a wide range of possible experimental realizations of different topological semimetal phases. Crucially, with no strain, the number of observable surface Fermi arcs in this material is 2 - the smallest number of arcs consistent with time-reversal symmetry.Comment: Published versio