Miracle-dz/UniFAR-FTUs huggingface dataset:
Losing Touch with Oneself: Depersonalisation Experiences Modulate Vicarious Affective Touch and Self Touch

Depersonalisation (DP) is characterized by distressing feelings of being detached from one’s self and body, often described as being “out of touch” with oneself. We conducted two online experiments looking at the relationship between non-clinical experiences of DP and vicarious affective touch and self touch. In Experiment 1 we found that people with lower occurrences of DP rate the perceived pleasantness of the imagined social touch as received by the self higher than if received by the other. By contrast, we found no difference in the perceived pleasantness of affective touch imagined as being received by the self vs the other in people with higher occurrences of DP experiences. In Experiment 2, we designed a new affective self-touch intervention in order to explore the effect of affective self-touch stroking on one’s dorsal forearm on the perceived pleasantness and vividness of tactile experiences as being received by the self and others . We found that both low and high DP participants, following the affective self-touch intervention, report signi�cantly higher ratings of vividness of tactile perception. These �ndings may have key implications for potential sensory tactile-based interventions for people experiencing distressing feelings of DP.
Strategies adopted by Aphanizomenon os-aquae in response to phosphorus de�ciency and their role on growth

Background The N2-xing cyanobacterium, Aphanizomenon os-aquae is a globally distributed bloom causing species that degrades water quality of fresh and marine water bodies. Overcoming phosphorus (P) de�ciency is one of the ecological advantages for bloom forming cyanobacteria. It remains unclear to what extent can A. os-aquae alleviate P de�ciency by regulating P using strategies. Results Based on in situ observations of extracellular alkaline phosphatase (APase) in A. os-aquae via enzyme-labeled �uorescence in freshwater bodies in China, Poland and Czechia, we further investigated responses of isolated A. os-aquae to different P supplies (dissolved inorganic P (Pi) as +DIP, dissolved organic α-glycerophosphate and β-glycerophosphate as +DOPα and +DOPβ, P-free condition as P-depleted). The signi�cantly negative relationships between percentage of APase producing cells and soluble reactive P concentration in both �elds and cultures suggested that the excretion of APase in cyanobacterium was regulated by ambient Pi supply. Suffering from P de�ciency in the P-depleted treatments, A. os-aquae showed the highest APase activity but a vigorous growth at the early culture stage, which might also bene�t from the formation of polyphosphate body (PPB) and the decrease of cell P quota. In the +DOP treatments, the coordination of dissolved DOP mineralization and continuous prompt utilization of PPB might contribute to a maintenance but not reproduction of A. os-aquae when relying on DOP, since the speci�c growth rate kept around 0 cells L-1 day-1 at the second half culture period and the highest cell density reached only 13.38% of that in +DIP treatments while photochemical e�ciency was comparable during the whole experiment. Luxury uptake of phosphate as PPB in the +DIP treatments was consistent to the canonical view of polyphosphate as P storage. Conclusion A. os-aquae could achieve an instantaneous growth in response to P de�ciency with the coordination of P utilization strategies, while it maintained a long-term sustainable growth but not reproduction under sole DOP supply. Persistent and active reproduction could only
Exploring Factors Affecting User Satisfaction and Behavioral Intention towards Telemedicine Services among Gen-Z and Millennials in Indonesia: A PLS-SEM Study on Alodokter Application (preprint)

Telemedicine has become increasingly important in healthcare, especially with the COVID-19 pandemic. Alodokter, one of the pioneers of health applications providing telemedicine services in Indonesia since 2014, has gained significant attention. Younger generations–Millennials and Gen Z–are more fluent in using technology. However, previous study shows that older generations (Gen X) is more satisfied in using telemedicine compared to younger generations. This study aims to identify the factors influencing user satisfaction and behavioral intention towards Alodokter's telemedicine service application usage among Millennials and Gen-Z in Indonesia. A survey was conducted on 160 respondents using a purposive sampling technique. The data was analyzed using the PLS-SEM based method with the SmartPLS MacOS application version 3.2. 9. The study focused on examining the relationships between the variables of behavioral intention, customer satisfaction, and factors including performance expectancy, effort expectancy, price value, and social influence. The study findings indicate that customer satisfaction positively affects behavioral intention. Performance expectancy, effort expectancy, price value, and social influence positively impact customer satisfaction. Price value was shown to have the most positive influence on behavioral intention. The study provides insights into the factors influencing user satisfaction and behavioral intention towards telemedicine service application usage among younger generations in Indonesia. The results can be used to improve telemedicine services and enhance the experience of users, particularly Millennials and Gen-Z.
French discourse markers in Shaba Swahili conversations

Acknowledgments* Data for this study were gathered during fieldwork in Lubumbashi (DR Congo) carried out in 1991 and 1992. Fieldwork was made possible by grants from the Institute for Functional Research into Language and Language Use and the Netherlands Foundation for the Advancement of Tropical Research. The support of these institutions is hereby gratefully acknowledged. I would like to thank Yael Maschler and an anonymous IJB reviewer for their critical and helpful remarks on an earlier draft of this paper. All usual disclaimers apply.
DeficiencyMultiple Cerebral Aneurysms in Factor VII

Summary: A rare case of multiple cerebral aneurysms and factor VII deficiency is presented. The authors hypothesize a possible combined genetic defect similar to that of other conditions with clotting disorders. Different treatment options are discussed for factor VII deficiency in particular and multiple cerebral aneurysms in general. The authors advise treatment of all detected aneurysms in case of a subarachnoid hemorrhage rather than only treatment of the ruptured aneurysms in order to immediately start the so-called triple-H therapy.
ACF-GSVM: CASCADE AGGREGATE CHANNEL FEATURE WITH GABOR FILTERS AND SUPPORT VECTOR MACHINE FOR ENHANCED FACE DETECTION

Face detection has recently attracted a lot of attention because of the groundbreaking work of Viola and Jones. Despite the efforts to improve the performance using several subsequent enhancements, feature representation for face detection remains unsuitable for handling faces with a complicated appearance in an efficient and effective manner. In order to solve this dilemma, we look into the concept of face detection that elaborates the channel overview in a variety of ways, such as using gradient, oriented gradient, histograms, which are known to be efficient for decoding uncomplicated sound information. Consequently, the researchers suggest a novel hybridized and improved face detection method that addresses the problems associated with face detection schemes by utilizing an aggregate channel feature with Gabor filters and a support vector machine, called the ACF-GSVM model. The procedure for improving the face detection is based on a cascade of an aggregate channel feature with Gabor filters and a support vector machine, where the bounding boxes of the face region are initially detected with the use of aggregate channel features. The key decision is made by using Gabor filters and a support vector machine that identifies which bounding boxes belong to the face region. Experiments on the CASIA-FaceV5 database with the proposed ACF-GSVM face detection scheme showed that the accuracy rate it achieved in face detection was 96.6%. This study demonstrates the effectiveness of the proposed method.
Unveiling the nature of INTEGRAL objects through optical spectroscopy - VIII. Identification of 44 newly detected hard X-ray sources

(abridged) Hard X-ray surveys performed by the INTEGRAL satellite have discovered a conspicuous fraction (up to 30%) of unidentified objects among the detected sources. Here we continue our identification program by selecting probable optical candidates using positional cross-correlation with soft X-ray, radio, and/or optical archives, and performing optical spectroscopy on them. As a result, we identified or more accurately characterized 44 counterparts of INTEGRAL sources: 32 active galactic nuclei, with redshift 0.019 < z < 0.6058, 6 cataclysmic variables (CVs), 5 high-mass X-ray binaries (2 of which in the Small Magellanic Cloud), and 1 low-mass X-ray binary. This was achieved by using 7 telescopes of various sizes and archival data from two online spectroscopic surveys. The main physical parameters of these hard X-ray sources were also determined using the available multiwavelength information. AGNs are the most abundant population among hard X-ray objects, and our results confirm this tendency when optical spectroscopy is used as an identification tool. The deeper sensitivity of recent INTEGRAL surveys enables one to begin detecting hard X-ray emission above 20 keV from sources such as LINER-type AGNs and non-magnetic CVs.
A LATENCY-IMPROVED BLOCKCHAIN IMPLEMENTATION MODEL FOR NATION-WIDE ELECTRONIC VOTING SYSTEM

The application of blockchain technology has been considered a breakthrough for the electronic voting system research domain, given that the technology has the potentials to fix the issues of ballot confidentiality, single point of failure, and compromise of election results integrity that have been regarded as the bane of electronic voting systems. However, blockchain technology itself is not without some concerns. Chiefly amongst these concerns are latency and scalability. This paper aims to showcase existing efforts to improve the latency of a blockchain network and to present a Blockchain Implementation Model that improves the latency concern in electronic voting systems, using the Nigeria’s Independent National Electoral Commission as a case study. The study evolved a latency-improved blockchain model that showcases the latency performance of the proposed blockchain-based e-voting system. The result showed a 99.36 percent improvement on the existing blockchain-based e-voting system.
COMPARATIVE EVALUATION OF CARDIOVASCULAR DISEASE USING MLR AND RF ALGORITHM WITH SEMANTIC EQUIVALENCE

Coronary artery disease is a highly intricate medical condition that affects a significant portion of the global population. It is even being referred to as a silent killer because it results in the death of a person with no obvious symptoms. The timely and accurate detection of heart disease is crucial in the healthcare industry, especially within the cardiology domain, as it enables effective treatment and management of the condition. Based on Machine learning techniques, an accurate and efficient model will be created to diagnosis heart disease. The machine learning models for classification will be developed using Multiple Linear Regression Algorithm and Random Forest Algorithm. Heart datasets were obtained from five countries: Cleveland, Hungary, Swiz, LongBeach, and Statlog, and datasets were analyzed using the Random Forest algorithm, KNN, Naive Bayes, SVM Algorithm and Multiple Linear Regression Algorithm to extract an intelligent pattern for forecasting the risk of heart disease. The accuracy of the MLR and RF models will be tested, and the best model will be deployed in health-care settings to diagnose cardiac disease.
Impact of disproportionality in severe secondary mitral regurgitation according to disease etiology

Aims Disproportionality in secondary mitral regurgitation (MR) provides insight into MR quanti�cation in transcatheter edge-to-edge repair (TEER) candidates. Although secondary MR has two major etiologies, ischemic cardiomyopathy (ICMP) and dilated cardiomyopathy (DCMP), distinguishing analysis between these two etiologies has been insu�cient. We sought to determine the prognosis of disproportional MR in each disease etiology and analyze the baseline characteristics. Methods and results From 2009 to 2019, in Samsung Medical Center, South Korea, 207 patients with severe secondary MR (median age 69 years old, median left ventricular ejection fraction [LVEF] 27.3%) were collected. The cut-off point for disproportional MR was the median value of regurgitant volume (RV)/left ventricular end-diastolic volume (LVEDV), which was 0.17. The primary endpoint was all-cause death. In this study, we analyzed 1) the prognosis of severe secondary MR based on proportional and disproportional MR and 2) the prognosis of disproportional MR based on etiology of dilated cardiomyopathy or ischemic cardiomyopathy. In survival analysis, the disproportional MR group had a worse prognosis in all-cause death (hazard ratio [HR] 2.013, 95% CI [1.254 - 3.230], log-rank p-value = 0.004). In subgroup analysis based on etiology, the disproportional MR group showed a signi�cantly higher risk of all-cause death (HR 3.493, 95% CI [1.457 - 8.375], log-rank p-value = 0.005) in DCMP. On the other hand, there was no signi�cant difference in all-cause death according to disproportionality in ICMP. Conclusion In severe secondary MR, disproportional MR has a worse prognosis than proportional MR due to age and comorbidities, and this difference is more prominent in DCMP than ICMP.
Digitalisation and Organisational Value: A Digital Capability Digitalisation and Organisational Value: A Digital Capability Renewal Framework Renewal Framework

The rapidly changing business environment compels businesses to invest in digitalisation. Whilst the investment in digitalisation is growing, businesses struggle to realise the strategic benefits of digitalisation. To address this problem, this paper introduces a digital capabilities renewal framework. Drawing from the dynamic capability theory, we argue that to generate and sustain business value, an organisation’s effort must be directed to the capability renewal process – a process of reconfiguring and realigning digital capabilities to develop higher-order dynamic capabilities. We present this argument in a nomological net that binds together the ordinary capabilities and managerial actions, the digital capability renewal process, and the dynamic capabilities and organisational value constructs. We further develop a set of propositions. The paper lays the foundation for investigating the activities and impacts of the digital capability renewal process. Future research can test and validate the proposed framework in empirical settings.
Biowaste mediated synthesis of silver nanoparticles and its effect on food preservation

- Silver nanoparticles (AgNPs) are antimicrobial agendas with broad -spectrum activity including against pathogens and spoilage bacteria However, their mechanism of action is not fully understood. Today, there is growing scientific interest in his AgNP Biosynthesis, focusing on extracellular biosynthesis by microbial cells. AgNP can be incorporated into biodegradable and can be non-biodegradable polymers for the production of food packaging with antimicrobial properties, resulting in improved safety and longer shelf life. However, for new food packaging materials with AgNPs, it is important to conduct migration studies based on effective concentrations for incorporation into packaging materials. The demand for adding the shelf life of fresh food as well as the need for guarding the food against food borne infections warrant the demand for adding the shelf life of fresh food. The objections of Nano particles into packaging material can enhance the preservation of perishable foods, Gray nanoparticles (AgNP), in particular, have antibacterial, anti-mold, anti-yeast and anti-viral conditioning can be bedded into the biodegradable packaging accoutrements for this purpose.
MATHEMATICAL MODELS AND METHODS FOR SOLVING THE PROBLEM OF EVACUATION

The problem of evacuation of people from closed premises such as universities, colleges and schools is considered. The peculiarity of this work lies in the formation of an integrated approach for organizing the evacuation process in peacetime as a training for an emergency. A conceptual diagram of an evacuation system is proposed that uses heterogeneous sources for receiving and transmitting information about the onset of an emergency. The input and output sources for receiving and transmitting information about the number of people in the building are determined. The main purpose of the system is to form an operational evacuation plan in real time. The optimal solution to the problem of maximum network flow is implemented using a game-theoretic approach. A mathematical model has been developed for the optimal distribution of the flow along the grindshill network with the analysis of the flow formation and the characteristics of the ways of people moving in closed spaces. A game-theoretic approach and mathematical methods of the theory of hydraulic networks for finding an equilibrium state in flow-distribution networks have been developed. An algorithm for solving the evacuation problem using the graph approach is proposed.
Edinburgh Research Explorer Visually Grounded Meaning Representations

—In this paper we address the problem of grounding distributional representations of lexical meaning. We introduce a new model which uses stacked autoencoders to learn higher-level representations from textual and visual input. The visual modality is encoded via vectors of attributes obtained automatically from images. We create a new large-scale taxonomy of 600 visual attributes representing more than 500 concepts and 700K images. We use this dataset to train attribute classiﬁers and integrate their predictions with text-based distributional models of word meaning. We evaluate our model on its ability to simulate word similarity judgments and concept categorization. On both tasks, our model yields a better ﬁt to behavioral data compared to baselines and related models which either rely on a single modality or do not make use of attribute-based input.
Antipsychotic-associated weight gain: management strategies and impact on treatment adherence

Antipsychotic-induced weight gain is a major management problem for clinicians. It has been shown that weight gain and obesity lead to increased cardiovascular and cerebrovascular morbidity and mortality, reduced quality of life and poor drug compliance. This narrative review discusses the propensity of various antipsychotics to cause weight gain, the pharmacologic and nonpharmacologic interventions available to counteract this effect and its impact on adherence. Most antipsychotics cause weight gain. The risk appears to be highest with olanzapine and clozapine. Weight increases rapidly in the initial period after starting antipsychotics. Patients continue to gain weight in the long term. Children appear to be particularly vulnerable to antipsychotic-induced weight gain. Tailoring antipsychotics according to the needs of the individual and close monitoring of weight and other metabolic parameters are the best preventive strategies at the outset. Switching to an agent with lesser tendency to cause weight gain is an option, but carries the risk of relapse of the illness. Nonpharmacologic interventions of dietary counseling, exercise programs and cognitive and behavioral strategies appear to be equally effective in individual and group therapy formats. Both nonpharmacologic prevention and intervention strategies have shown modest effects on weight. Multiple compounds have been investigated as add-on medications to cause weight loss. Metformin has the best evidence in this respect. Burden of side effects needs to be considered when prescribing weight loss medications. There is no strong evidence to recommend routine prescription of add-on medication for weight reduction. Heterogeneity of study methodologies and other confounders such as lifestyle, genetic and illness factors make interpretation of data difficult.
Antipsychotic-associated weight gain: management strategies and impact on treatment adherence

: Antipsychotic-induced weight gain is a major management problem for clinicians. It has been shown that weight gain and obesity lead to increased cardiovascular and cere-brovascular morbidity and mortality, reduced quality of life and poor drug compliance. This narrative review discusses the propensity of various antipsychotics to cause weight gain, the pharmacologic and nonpharmacologic interventions available to counteract this effect and its impact on adherence. Most antipsychotics cause weight gain. The risk appears to be highest with olanzapine and clozapine. Weight increases rapidly in the initial period after starting antipsychotics. Patients continue to gain weight in the long term. Children appear to be particularly vulnerable to antipsychotic-induced weight gain. Tailoring antipsychotics according to the needs of the individual and close monitoring of weight and other metabolic parameters are the best preventive strategies at the outset. Switching to an agent with lesser tendency to cause weight gain is an option, but carries the risk of relapse of the illness. Nonpharmacologic interventions of dietary counseling, exercise programs and cognitive and behavioral strategies appear to be equally effective in individual and group therapy formats. Both nonpharmacologic prevention and intervention strategies have shown modest effects on weight. Multiple compounds have been investigated as add-on medications to cause weight loss. Metformin has the best evidence in this respect. Burden of side effects needs to be considered when prescribing weight loss medications. There is no strong evidence to recommend routine prescription of add-on medication for weight reduction. Heterogeneity of study methodologies and other confounders such as lifestyle, genetic and illness factors make interpretation of data difficult.
A system for the study of roots 3D kinematics in hydroponic culture: a study on the oscillatory features of root tip

Background The root of a plant is a fundamental organ for the multisensory perception of the environment. Investigating root growth dynamics as a mean of their interaction with the environment is of key importance for improving knowledge in plant behaviour, plant biology and agriculture. To date, it is di�cult to study roots movements from a dynamic perspective given that available technologies for root imaging focus mostly on static characterizations, lacking of temporal and three-dimensional (3D) spatial information. This paper describes a new system based on timelapse for the 3D reconstruction and analysis of roots growing in hydroponics. Results The system is based on infrared stereo-cameras acquiring time-lapse images of the roots for 3D reconstruction. The acquisition protocol guarantees the root growth in complete dark while the upper part of the plant grows in normal light conditions. The system extracts the 3D trajectory of the root tip and a set of descriptive features in both the temporal and frequency domains. The system has been used on Zea mays L. (B73) during the �rst week of growth and shows good inter-reliability between operators with an Intra Class Correlation Coe�cient (ICC) > 0.9 for all features extracted. It also showed measurement accuracy with a median difference of < 1 mm between computed and manually measured root length.