Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated care models for older adults with depression and physical multimorbidity: a scoping review

Objective: Multimorbidity, the coexistence of multiple chronic conditions occurring in one person at the same time, where one is not a known complication of the other, is a growing challenge in the care for older people with mental illness. In order to address both physical and mental illnesses in older people, integrated care management is required. The purpose of this scoping review was to provide a comprehensive overview of integrated care models for older adults (60+) with depression and physical multimorbidity. We identified the core components of the examined integrated care models and mapped the reported outcomes and implementation strategies. Methods and analysis: We followed the methodology of Arksey and O’Malley’s. MEDLINE, EMBASE, CINAHL and Cochrane Library were searched independently by two reviewers from inception to May 2022. Studies composed in English or Dutch concerning integrated care interventions for older adults with major depression and physical multimorbidity were included. We used the micro-level SELFIE framework to map the core concepts of integrated care models. Outcomes were divided in person-centered and service themes. Results: After title and abstract and subsequent full-text screening, 38 studies were included describing 13 different care models. The majority (n=21) were randomized controlled trials, followed by observational studies (n=6), study protocols (n=5), qualitative studies (n=4), and feasibility studies (n=2). Studies were conducted in the North-America (n=28), Europe (n=6), Asia (n=3) and Australia (n=1). In all care models, a multidisciplinary team with a care coordinator was involved. Also treatment interaction, continuity of care, individualized care planning, tailored holistic assessment and self-management support were elements of all care models. Informal care giver involvement and shared decision making were less often described as core elements. Discrepancy was detected in the information systems and technology that different care models used. Only seven care models reported on financial aspects of the intervention, e.g. the reimbursement on participation or the provision of financial incentives. A total of 32 different outcomes were evaluated in the primary studies. Patient outcomes, e.g. functional status and depression symptoms, are well described by all care models. In contrast, little attention is paid to service outcomes such as emergency department visits or therapy attendance. Only two studies briefly described the implementation strategies used in the study. Conclusion: The core elements that comprise integrated care models are diverse. Future studies should focus more on implementation aspects of the intervention and describe financial parts, e.g. the cost of the intervention for the healthcare user, more transparently. Key words: Collaborative care, integrated care, psychosomatic medicine, geriatric psychiatry, care models
Targeted Transcriptional Activation in Plants Using a Potent Dead Cas9–Derived Synthetic Gene Activator

Genetic tools for specific perturbation of endogenous gene expression are highly desirable for interrogation of plant gene functions and improvement of crop traits. Synthetic transcriptional activators derived from the CRISPR/Cas9 system are emerging as powerful new tools for activating the endogenous expression of genes of interest in plants. These synthetic constructs, generated by tethering transcriptional activation domains to a nuclease‐dead Cas9 (dCas9), can be directed to the promoters of endogenous target genes by single guide RNAs (sgRNAs) to activate transcription. Here, we provide a detailed protocol for targeted transcriptional activation in plants using a recently developed, highly potent dCas9 gene activator construct referred to as dCas9‐TV. This protocol covers selection of sgRNA targets, construction of sgRNA expression cassettes, and screening for an optimal sgRNA using a protoplast‐based promoter‐luciferase assay. Finally, the dCas9‐TV gene activator coupled with the optimal sgRNA is delivered into plants via Agrobacterium‐mediated transformation, thereby enabling robust upregulation of target gene expression in transgenic Arabidopsis and rice plants. © 2019 by John Wiley & Sons, Inc.
Identifying Cross-User Privacy Leakage in Mobile Mini-Apps at a Large Scale

With the characteristics of free installation and rich functionalities, mobile mini-apps have become more and more popular in people’s daily life. A large amount of sensitive personal data is thus involved in them and shared across users for providing various services, which raises great privacy concerns. However, few researchers have paid attention to the potential privacy risks that may exist when user data is shared across users in mobile mini-apps. In this paper, we introduce a novel privacy risk that is brought forward by cross-user personal data over-delivery (denoted as XPO) in mobile mini-apps. Such a discovered privacy risk is demonstrated to be able to cause serious leakage of diverse user data. To detect XPO risk, a dynamic and lightweight mini-app analysis framework – XPOScope is proposed. XPOScope is able to automatically identify XPO risk at a large scale. By applying it to 4,273 mini-apps hosted on three popular platforms, i.e., WeChat, Baidu and Alipay, XPOScope reported 71 vulnerable ones, with a precision of 92.21% and a recall of 80.68%. In addition to the mere exposure of diverse private user data, case studies performed show that XPO in mini-apps can further lead to impersonation attacks, the infringement of employees’ privacy, economic loss and even the leakage of sensitive business secrets. The results call for the awareness and actions of mobile mini-app developers to secure cross-user personal data delivery. The code of this work is available at https://github.com/ppflower/XPOScope.
Deformation pattern during normal faulting: A sequential limit analysis

We model in 2‐D the formation and development of half‐graben faults above a low‐angle normal detachment fault. The model, based on a “sequential limit analysis” accounting for mechanical equilibrium and energy dissipation, simulates the incremental deformation of a frictional, cohesive, and fluid‐saturated rock wedge above the detachment. Two modes of deformation, gravitational collapse and tectonic collapse, are revealed which compare well with the results of the critical Coulomb wedge theory. We additionally show that the fault and the axial surface of the half‐graben rotate as topographic subsidence increases. This progressive rotation makes some of the footwall material being sheared and entering into the hanging wall, creating a specific region called foot‐to‐hanging wall (FHW). The model allows introducing additional effects, such as weakening of the faults once they have slipped and sedimentation in their hanging wall. These processes are shown to control the size of the FHW region and the number of fault‐bounded blocks it eventually contains. Fault weakening tends to make fault rotation more discontinuous and this results in the FHW zone containing multiple blocks of intact material separated by faults. By compensating the topographic subsidence of the half‐graben, sedimentation tends to slow the fault rotation and this results in the reduction of the size of the FHW zone and of its number of fault‐bounded blocks. We apply the new approach to reproduce the faults observed along a seismic line in the Southern Jeanne d'Arc Basin, Grand Banks, offshore Newfoundland. There, a single block exists in the hanging wall of the principal fault. The model explains well this situation provided that a slow sedimentation rate in the Lower Jurassic is proposed followed by an increasing rate over time as the main detachment fault was growing.
Spatial Attention-Enhanced EEG Analysis for Profiling Consumer Choices

Over the years, research in neuroscience-driven marketing has progressively delved into the conscious and subconscious behaviors of consumers. Existing Electroencephalography (EEG)-based studies related to consumer preferences toward products are not comprehensive. Due to non-stationarity issues of EEG, a significant variance is observed in inter-trial and inter-session EEG signals of a subject, which leads to challenges in building a universal consumer preference model across diverse subjects, sessions, and tasks. Transfer learning mitigates this challenge by utilizing data or knowledge from similar subjects, sessions, or tasks to improve the learning process for a new subject, session, or task, thereby enhancing overall model performance. Moreover, high-dimensional EEG features often lead to poor classification results. Therefore, selecting meaningful or refined features is of utmost importance for classification. Therefore, we propose a robust EEG-based neuromarketing framework combining deep transfer learning, spatial attention models, and deep neural networks. The proposed framework predicts the consumer choices (in terms of “likes” and “dislikes”) for e-commerce products. Initially, the knowledge distillation is performed from the pre-trained network to the proposed model, and the model is trained on the connectivity features of EEG. Next, the attention-based features are extracted from high-level connectivity features using the spatial attention model (Convolutional Block Attention Module: CBAM). CBAM extracts the attention feature maps along channel and spatial dimensions for adaptive feature refinement. The refined features improve the classification accuracy. Finally, the attention-based features are passed to the 2D CNN-based deep learning model to evaluate consumer choices. The proposed model achieves 95.60% classification accuracy with the experimental dataset. The proposed model achieves a significant improvement of 2.60% over the existing neuromarketing-based studies.
Effectiveness of Balance Training and Strengthening Exercise on Pain and Functional Performance among the Athletes with Ankle Sprain

Background:. Ankle sprain happens more regularly in the athletic population. It results from the straining of ankleligaments or collagen which produces the partial or full disruption of the ligaments fibers. Ankle injuries mostcommonly occur in the climbing of the wall ,indoor volleyball and events that occur in the grassland. This studywas designed to inspect the effectiveness of balance training and strengthening exercise among the athletes withankle sprain.Purpose: To compare the effectiveness of balance training and strengthening exercise on pain and functionalperformance among the athletes with ankle sprain.Materials and Methods: Total of 50 participants were selected according to the inclusion and exclusion criteria from theortho speciality Neha clinic. The participants were treated for four weeks. The study duration from October 2022 to july 2023.Subjects willing to participate were randomly allocated into two groups: balance training group and strengthening exercisegroup. All the subjects underwent pretest measurement with VAS, FAAM and the same procedure repeated for post-test at theend of 4 weeks.Results: The collected data was statistically analyzed using an unpaired t-test. When comparing the balance training group tothe strengthening exercise group, the balance training group indicates more significant effects (p<0.0001) than the strengtheningexercise in lowering pain and improving the functional performance, as assessed by VAS and FAAM.Conclusion: Balance training was found to be more effective than strengthening exercise in reducing pain andimproving functional performance among athletes with ankle sprain.
Volatiles and Exsolved Vapor in Volcanic Systems

The role of volatiles in magma dynamics and eruption style is fundamental. Magmatic volatiles partition between melt, crystal, and vapor phases and, in so doing, change magma properties. This has consequences for magma buoyancy and phase equilibria. An exsolved vapor phase, which may be distributed unevenly through reservoirs, contains sulfur and metals that are either transported into the atmosphere or into ore deposits. This article reviews the controls on volatile solubility and the methods to reconstruct the volatile budget of magmas, focusing particularly on the exsolved vapor phase to explore the role of volatiles on magma dynamics and on eruption style.
The Influence of Micro-Hexapod Walking-Induced Pose Changes on LiDAR-SLAM Mapping Performance

Micro-hexapods, well-suited for navigating tight or uneven spaces and suitable for mass production, hold promise for exploration by robot groups, particularly in disaster scenarios. However, research on simultaneous localization and mapping (SLAM) for micro-hexapods has been lacking. Previous studies have not adequately addressed the development of SLAM systems considering changes in the body axis, and there is a lack of comparative evaluation with other movement mechanisms. This study aims to assess the influence of walking on SLAM capabilities in hexapod robots. Experiments were conducted using the same SLAM system and LiDAR on both a hexapod robot and crawler robot. The study compares map accuracy and LiDAR point cloud data through pattern matching. The experimental results reveal significant fluctuations in LiDAR point cloud data in hexapod robots due to changes in the body axis, leading to a decrease in map accuracy. In the future, the development of SLAM systems considering body axis changes is expected to be crucial for multi-legged robots like micro-hexapods. Therefore, we propose the implementation of a system that incorporates body axis changes during locomotion using inertial measurement units and similar sensors.
Alterations of Gastrointestinal Microbe Composition in Various Human Diseases and Its Significance in the Early Diagnosis of Diseases

A 100 trillion bacteria, viruses, fungi, and archaea make up the human gut microbe. It has co-evolved with its human host and carries out essential tasks that improve general health. The relationship between gastrointestinal microbes and human health has been a growing field of interest and research in recent times. The gastrointestinal microbes are connected by complex networks and connections, and the host has given birth to the gut-microbe-brain axis, which shows the crucial effect that this circumstance could have on the health and diseases of the brain and spinal cord (or the central nervous system [CNS]). The microbe and the CNS interact bi-directionally via autonomic, neuroendocrine, gastrointestinal, and immune system pathways. The gut microbe has been connected to a range of gastrointestinal and extra-gastrointestinal diseases. The recent investigation supports the suspicion that the gut-microbe-brain axis could play a role in neuropsychiatric disorders including depression, dementia, post-traumatic stress disorder, anxiousness, bipolar disorder, schizophrenia, and obsessive-compulsive disorder, alongside chronic host illnesses such as obesity, diabetes, and inflammation. Studies point to gut microorganisms as possible biomarkers for a wide range of mental health issues. Changes in the gut microbe may be a crucial factor in the onset and advancement of non-alcoholic fatty liver damage. Gut microbes have been seen to influence microglia’s response to the CNS's regional signals and thus to pain and inflammation. Data suggest that altering the gut microbe in those with chronic pain may be a successful method for reducing pain. Numerous investigations have documented alterations in the gut microbes made in Alzheimer patients and schizophrenic patients. The risk of breast cancer can be reduced by restoring gut microbe homeostasis and reducing systemic estrogen levels.
Reassessing the warming impact of methane emissions from Irish livestock using GWP*: historical trends and sustainable futures

Methane from livestock production contributes significantly to Ireland’s greenhouse gas emissions. Methane emissions are generally expressed as carbon dioxide equivalents (CO2e) using the global warming potential (GWP) metric, but this conversion may result in an inaccurate assessment, because methane has a much shorter atmospheric lifespan than CO2. This study calculated the CO2e of methane emissions from Irish livestock using the GWP and GWP* metrics, the latter of which accounts for the short-lived nature of atmospheric methane. Methane emissions from all Irish livestock (1961–2020) were included and three projected scenarios to 2050 were hypothesised: increasing emissions, decreasing emissions and constant emissions. The CO2e of methane from Irish livestock was found to be influenced by changes in the rate of emission over the preceding decades. Using the GWP* metric, declining populations of donkeys and horses from 1961 to 2000 were shown to cause atmospheric removals of methane when expressed as CO2e. Increasing populations of swine and non-dairy cattle (in response to industrial changes and European Union [EU] regulations) saw significant increases in the CO2e of methane emissions from these sources. Milk quotas caused a significant reduction in the CO2e of methane emissions from dairy cows, and atmospheric removals were observed in the years 1990–2012. GWP* indicated that the constant and decreasing future emission scenarios gave more significant reductions in CO2e than the GWP. These results indicate the importance of the effect of emission rate on the CO2e of methane from Irish livestock, which is accounted for using GWP*, but not by the conventional GWP.
Optimal allocation of public parking spots in a smart city: problem characterisation and first algorithms

ABSTRACT Having a mechanism to mathematically model the problem of the optimal allocation of parking spots within cities could bring great benefits to society. According to the International Parking Institute, about 38% of the cars circulating throughout a city are looking for available parking spots, leading to increased pollution and subsequent health problems, as well as economic losses due to wasted man-hours. In the work presented here, a new mathematical model describing the problem of the optimal allocation of parking spots is proposed, along with an evolutionary algorithm to demonstrate how this model can be used in practice. A simulated annealing algorithm was implemented to test the effectiveness of this approach. The proposed strategy will allow users to find parking more quickly and easily, as well as lead to new services for the hot-topic of smart mobility. For the definition of the problem, a real map of the city of Malaga, Spain, was used along with Sumo software to carry out the simulations. The results clearly demonstrated that the proposed mechanism is capable of minimising the global cost of parking, implying a direct benefit for users.
Analytical and statistical approach for evaluating the effects of a river barrage on river–aquifer interactions

The construction of a river barrage can increase groundwater levels upstream of the barrage during the rainy season. Analytical and statistical approaches were applied to evaluate the relationship between groundwater and river water at the Changnyeong–Haman river barrage in Korea using time series data of water level and electrical conductivity from June 2011 to September 2014. An artificial neural network based time series model was designed to filter out the effect of rainfall from the groundwater level data in the study area. Aquifer diffusivity and river resistance were estimated from the analytical solution of a one‐dimensional unit step response function by using the filtered groundwater level data. River resistance increased in response to groundwater level fluctuations. Cross‐correlation analyses between the groundwater and the river water showed that the lag time increased during the observation period for both the water level and the electrical conductivity while the cross‐correlation function declined for the same period. The results indicated that a constant river stage maintained at the river barrage can weaken the hydrologic stress and reduce the exchange of material between the river and the adjacent aquifer because of the deposition of fine sediment on the river bottom and walls. Copyright © 2016 John Wiley & Sons, Ltd.
ATMOSPHERIC N DEPOSITION TO THE COASTAL AREA OF THE BLACK SEA: SOURCES, INTRA-ANNUAL VARIATIONS AND IMPORTANCE FOR BIOGEOCHEMISTRY AND PRODUCTIVITY OF THE SURFACE LAYER

Atmospheric precipitations can be an important source of nutrients to open and coastal zones of marine ecosystem. Jickells [1] has published that atmospheric depositions can support 5-25% of nitrogen required to primary production. Bulk atmospheric precipitations have been collected in a rural location at the Black Sea Crimean coast – Katsiveli settlement, and an urban location – Sevastopol city. Samples have been analyzed for inorganic fixed nitrogen (IFN) – nitrate, nitrite, and ammonium. Depositions have been calculated at various space and time scales. The monthly volume weighted mean concentration of IFN increases from summer to winter in both locations. A significant local source of IFN has been revealed for the urban location and this source and its spatial influence have been quantified. IFN deposition with atmospheric precipitations is up to 5% of its background content in the upper 10 m layer of water at the north-western shelf of the Black Sea. Considering Redfield C:N ratio (106:16) and the rate of primary production (PP) in coastal areas of the Black Sea of about 100-130 g C m-2 year-1 we have assessed that average atmospheric IFN depositions may intensify primary production by 4.5% for rural locations, but this value is increased many-fold in urban locations due to local IFN sources.
In Silico Design and Evaluation of Novel Cell Targeting Melittin-Interleukin-24 Fusion Protein: A potential Drug Candidate Against Breast Cancer

Fusion proteins are designed to achieve new functionality or improved properties synergistically by incorporating multiple protein domains into one complex. The fusion of two genes to translate a recombinant protein for cancer treatment can enhance the bioactivity of drug and can introduce novel drug candidate with wide range of applications in pharmaceuticals and biotechnology. Interleukin-24 (IL-24) is a novel cancer growth-suppressing and apoptosis inducing cytokine while melittin is a natural honeybee derived cationic polypeptide having anti-tumor activity against breast cancer cells. The current study was aimed to perform in silico design and analyses of a melittin-IL-24 fusion protein against breast cancer. The amino acid sequences of the IL-24 and melittin peptide were used to design the fusion protein via a rigid linker. Using the online softwares we predicted the secondary and tertiary structures along with physicochemical properties of the designed fusion protein. The validation and quality of the fusion protein was confirmed by Rampage and ERRAT2. The top ranked structure from I-TASSER showed 18.1KD molecular weight by ProtParam, quality factor of 94.152 by ERRAT and a valid structure by Ramachandran plot with 88.5% residues in favoured region. The docking and simulation studies were performed using ClusPro and Desmond software. The quality, validity, interaction analysis and stability of the fusion protein depicted a functional molecule. The in silico analysis finding and expression predicted value of 0.86 in E. coli on SOLUPROT tool suggest that the melittin- IL-24 fusion protein can lead to develop a potent therapeutic drug against breast cancer.