Miracle-dz/UniFAR-FTUs huggingface dataset:
A world apart: Levels and determinants of excess mortality due to COVID-19 in care homes: The case of the Belgian region of Wallonia during the spring 2020 wave

BACKGROUND In Western countries, COVID-19 has been particularly deadly for care home residents. OBJECTIVE To understand the role of age and sex structures, health frailty, and contamination dynamics in COVID-19 mortality in populations living inside and outside care homes. METHODS We compared COVID-19 death data recorded in March-June 2020 in Wallonia (southern Belgium) for populations living inside and outside care homes, using annual death data (all-cause mortality in 2017) to assess the health condition of each population. RESULTS Sixty-four percent of COVID-19 deaths were residents in care homes, where the outbreak started after that in the external population, but at a faster pace. The death rate varied between 0 parts per thousand and 340 parts per thousand (mean 43 parts per thousand) per care home, increasing with the number of both residents and staff. All-cause and COVID-19 mortality rates increased exponentially with age but were much higher in care homes. The ratio of male (M) to female (F) death rates was 1.6 for all-cause mortality and 2.0 for COVID-19 mortality (both confirmed and suspected). The COVID-19 mortality reached 24% (M) and 18% (F) of the all-cause mortality rate in care homes, compared to 5% (M) and 4% (F) outside care homes. CONCLUSIONS The COVID-19 mortality rate was 130x higher inside than outside care homes, due to the near multiplicative effects of differences in the residents' age and sex structure (11x), health frailty (3.8x), and infection risk (probably 3.5x). CONTRIBUTION Care homes should be treated as a very specific population in epidemiological studies due to their extreme vulnerability to COVID-19.
Seismic response of multi-storey building using different vibration technique-A review

This review presents the high performance of failure-resistant structural device system for the sustainable and flexible buildings. Firstly, the motivation and basic principles as well as methodology of the developing device system are explicitly illustrated. Then, the structural detail and seismic response of base isolation systems, namely, lead Rubber Bearing (LRB), HDLRB isolators, viscous damper base isolator (BIPD) and sliding bearing isolator (BISS) are summarized. The theoretical and experimental study results was shown that all four types of isolator system can be able to minimize damage after seismic an earthquake to the structural system. The viscous damper devices and energy dissipate as well as viscoelastic and fluid viscous dampening can be able to enhance the energy dissipation capacity of structural system under an earthquake loading. A placement of L shape, shear walls at the structural configuration plan is given more efficient behavior under seismic load than all other placements of shear walls at the building’s configuration. Many numerical specimens of tunnel form buildings were constructed and modelled to analyze and interpreted the dynamic and static cyclic response of structures against seismic force. The deformation of the dynamic response of tunnel form building was smaller by using Carbon Fiber Reinforced Polymer (CFRP) repairing and retrofitting method. Contradictory, the usage of base isolations, energy dissipation devices, shear walls and tunnel form buildings can enhance the efficiency of structures under seismic force by reducing the economic cost saving in their construction.
IPO Underpricing and Real Estate Investment Trusts: Evidence from Japan

This study investigates the pricing of 75 initial public offerings (IPOs) of Japanese real estate investment trusts (J-REITs) during the period 2001-2018. We find that the issues are systematically underpriced with significantly positive initial-day returns. Consistent with underpricing explanations that rely on asymmetric information and valuation uncertainty, we show that the degree of underpricing is negatively related to leverage and varies with the type of property. In addition, our findings suggest that the J-REITs outperform several benchmarks over the 18 months following their IPOs. Contrary to the predictions of signaling theories of underpricing, we show that the initial-day returns are negatively related to the aftermarket performance. Supervisor: Professor Paolo Sodini
Effects of Long-Term Rehabilitation on Functional Independence Measures and the Elucidation of Novel Prognostic Factors in Patients with Post-Stroke

The incidence of stroke has increased worldwide and is not only a burden for patients but also a national and worldwide economic burden. In Japan, the incidence of stroke and the mortality for stroke have been decreased because of the educational programs for the sufficient blood pressure control such as the less intake of salt and the promotion of daily exercise by the government. Also, rehabilitation for post-stroke in Japan has provided the improvements of the motor and cognitive functions. Most attention has been focused on the early phase of rehabilitation, which has been shown to improve motor and cognitive disturbances. However, optimizing long-term rehabilitation to improve motor or cognitive dysfunction is also important. Furthermore, the factors that inhibit rehabilitation should be determined. Several studies focus on factors that attenuate or prevent improved motor and/or cognitive function during rehabilitation such as hypertension, age, sex, stroke severity and neglect. However, when we have paid an attention to such factors, we still recognize that the beneficial effects of rehabilitation are limited and we need to find the additional factors to inhibit the beneficial effects of rehabilitation. The functional independence measure (FIM) has been developed to provide a quantitative scale of activities of daily living: The FIM is an 18-item, 7-level scale developed to uniformly assess the severity of patient disability and the functional outcome of medical rehabilitation in terms of motor and cognitive abilities. We aimed to determine the impact of extensive and early-onset and long-term rehabilitation on motor and cognitive dysfunction and the clinical factors that might prevent the beneficial effects of rehabilitation on total, motor, and cognitive dysfunction in Japanese poststroke patients. We assessed the effects of extensive and early-onset rehabilitation for 1 year after discharge on FIM in post-stroke patients after the acute treatment of stroke. In addition, we investigated the clinical factors related to low total, motor, and cognitive FIMs.
THE EFFECT OF TOURISM ECONOMICS TOWARDS LIFE SATISFACTION AND ITS IMPACT ON PUBLIC’S INTENTIONS TO PARTICIPATE IN THE DEVELOPMENT OF NEW TOURIST DESTINATIONS

Purpose of this study is to measure the impact of tourism economics towards psychometric aspects such as; well-being, personal benefits, and life satisfaction of the community in order to predict the public's intention to participate in the development of tourist destinations. Designed by quantitative research using a scale of measurement was previously existed. The results of this study indicate there is no significant effect between economic benefits on the satisfaction of community life. Economic benefits will have an impact on the life satisfaction on local people and then be able to move the public's intention to participate in the development of new tourist destinations, if the communities feel the prosperity as well as theythink themselves are coming in useful in the tourist destinations development program. The implications shows that the size of the economy is not enough to be used to predict the satisfaction of life and further the public's intentions in the tourist destinations development, but necessary aspects in psychometric categories such as; well-being, personal benefit, and life satisfaction. Originality of this study is to filling the gap of study to involve psychometric aspects such as; well-being, personal benefits, and life satisfaction to predict people's intentions in the context of developing the new tourist destinations.
Well-ordered films of disk-shaped thermally activated delayed fluorescence molecules

Abstract. We fabricated well-ordered, crystalline mono- and multilayers of disk-shaped thermally activated delayed fluorescence (TADF) molecules such as 4CzIPN, 2CzPN, and 5CzBN. The slow deposition of these molecules on flat substrates such as Ag(111) at room temperature resulted in the formation of well-ordered and homogeneous monolayers. Moreover, the multilayer of the 4CzIPN was also found to be well-ordered and flat when deposited on highly oriented pyrolytic graphite (HOPG). The electronic states of the crystalline monolayer and multilayer of 4CzIPN were found to be nearly the same, suggesting that the electronic states of both layers are not altered significantly by adsorption on substrates. Indeed, we also confirmed the delayed fluorescence from the crystalline multilayer of 4CzIPN on the HOPG substrate even in an ambient condition. These results show promising applications of crystalline films of disk-shaped TADF-molecules such as 4CzIPN for organic light-emitting diodes devices with high outcoupling efficiency.
MULTIPLE LINEAR REGRESSION (MLR) MODELS USED FOR THE PREDICTION OF EXCESS THERMODYNAMIC PROPERTIES BASED ON EXPERIMENTAL DETERMINATION OF REFRACTIVE INDEX

In engineering, it is very important to have thorough knowledge of the thermodynamic and conveying properties of fluid mixtures, as they are mainly used to study the interactions that occur in fluids with several components, as well as to design various equipment for separation by distillation, fractional distillation and solvent extraction, and to achieve a scientific approach of the risk factors that affect separation processes. Our research group used the statistical processing of experimental data by the multiple linear regressions (MLR) method in order to estimate the excess molar volume starting from the experimental values of the refractive index for ternary systems. In this paper we will prove that this type of experimental data processing could also be used to predict other excess thermodynamic properties such as excess viscosity and excess surface tension (P E ). In order to achieve this goal, we will use both the literature data and experimental data obtained in our laboratory on the thermodynamic properties of certain fluid mixtures. The created mathematical models correlate the excess thermodynamic properties with the refractive index, the standard temperature and the fluid mixture composition: P E =A0+A1X1+A2X2+A3(T/298.15)+A4n, where X1 and X2 Corresponding author; e-mail: iuliana.birgauanu@yahoo.com 10 Iuliana Bîrgăuanu et al. are the molar fractions, T is the temperature expressed in Kelvin and n is the refractive index. These models are extremely useful in practice. The refractive index can be easily determined, with rather good accuracy and low substance consumption. These mathematical models also allow the determination of other properties, such as density, viscosity and surface tension, which are more difficult to determine by experimental methods.
A Study on identification of dog breeds through multi-class classification using Deep Learning techniques

Image classification, a discipline which over the years has made tremendous advancements with new and improved techniques continuously being implemented to improve the accuracy. With an enormous amount of effort being put into the field, multiclass classification has proven to be particularly challenging. Hence, in the present study the researcher focuses on achieving multiclass classification on dog breed identification using state of the art deep learning techniques. Having previously collaborated with NGO’s that managed dog adoptions, the researcher saw first-hand how wrongful breed classification affected the lives of these feeble beings by keeping them from getting the home they deserved. This in turn helped the researcher realize the urgency of such an identification system. Moreover, the researcher also focuses on a comparative study between deep learning and support vector machines which has proven to be particularly effective in binary classification. The results observed during the research inferred that ‘multiclass classification’ posed a problem even for deep learning however from the results observed from the comparative study, there was some light shed on how these problems could be tackled in the future. The results are presented.
A Study of Joint Graph Inference and Forecasting

We study a recent class of models which uses graph neural networks (GNNs) to improve forecasting in multivariate time series. The core assumption behind these models is that there is a latent graph between the time series (nodes) that governs the evolution of the multivariate time series. By parameterizing a graph in a differentiable way, the models aim to improve forecasting quality. We compare four recent models of this class on the forecasting task. Further, we perform ablations to study their behavior under changing conditions, e.g., when disabling the graph-learning modules and providing the ground-truth relations instead. Based on our findings, we propose novel ways of combining the existing architectures.
EVALUATION OF ANTI-MICROBIAL ACTIVITY OF CITRUS AURANTIUM AGAINST SOME GRAM POSITIVE AND NEGATIVE BACTERIAL STRAINS

The present investigation was carried out to evaluate the antibacterial activities of Citrus aurantium Linn. Dried leaf powder of Citrus aurantium was successively extracted with petroleum ether, chloroform and ethanol using Soxhlet and macerated to form water extract. All extracts were screened for its antibacterial using agar well diffusion method. The extracts showed antimicrobial activity were subjected to minimum inhibitory concentration (MIC) assay by two fold dilutions method. Petroleum ether, chloroform, ethanol and water extract exhibited in-vitro antibacterial activity.
RELATIONSHIP BETWEEN HELMINTHASIS AND GASTRIC CANCER: A SYSTEMATIC REVIEW

Introduction: helminths are parasitic worms able to produce diverse clinical manifestations in humans, mainly in the gut. Gastric cancer its a high incidence entity in Colombia, being the highland regions where its incidence is the highest in comparison with the lower incidence coastal region. From the above it is intended to determine the relationship between helminthiasis and the development of gastric cancer. Methodology: A systematic review was performed in four databases for studies evaluating the relationship between helminthiasis and the development of gastric cancer. Results: We included 16 articles from 929 records, with 11 articles reporting a positive relationship and 5 articles with negative relationship. Conclusions: Parasitic infections of the gastrointestinal tract by helminths promote TH-2 type immune responses and decrease TH-1 type that are involved in the progression of precancerous lesions associated with Helicobacter pylori infection. Keywords: Gastric cancer, Helminthiases, inflammation.
Numerical investigation of combustion process behind bluff bodies during separation

Numerical investigation of combustion process behind bluff bodies during separation A. M. Dostiyarov, D. R. Umyshev, Zh. S. Duissenbek, I. K. Iliev, H. I. Beloev, S. Ph. Ozhikenova Almaty University of Power Engineering and Telecommunications, Almaty, Kazakhstan Kazakh National Research Technical University, 22a Satpaev str, Almaty, Kazakhstan University of Ruse, Department of Thermotechnics, Hydraulics and Environmental Engineering 7017 Ruse, 8 Studentska Str. , Bulgaria
Isolation and Screening of Diesel-Degrading Bacteria from the Diesel Contaminated Seawater at Kenjeran Beach, Surabaya

Samples of contaminated seawater by diesel were taken at Kenjeran Beach Surabaya using aseptic technique. Isolation was conducted using serial dilution and spread method on nutrient agar (NA) media. The all bacteria colony were devided in to group based on with morphological characterization and gram staining. After that, those bacterial colonies were tested individually in NA media containing different concentration of diesel (2, 4, 6, 8, and 10%) for up to 7 days at 30C. The results showed that eight bacterial strains were isolated from diesel contaminated seawater in Kenjeran Beach Surabaya. Screening on diesel showed that all the isolation bacteria were capable of degrading diesel and bacteria with code of B and E haves highly percentage growth in compared to other bacterial isolation. In conclusion, bacteria with code of B and E have potential to be used in diesel bioremediation in contaminated seawater.
Ownership structure, agency problems of free cash flow and asymmetric information: Evidence from Brazil

Using financial and ownership data from Brazilian firms during the period of 1996 to 2010, we investigate how asymmetric information and agency costs of free cash flow impact the investment-cash flow sensitivity. We document that the largest ultimate shareholder’s cash flow rights have a constant relationship to investment-cash flow sensitivity when firms face both overinvestment and underinvestment problems. However, the excess of control rights over cash flow rights have different behavior on investment decision. We find an inverted U-shaped relationship between the excess of control rights and investment-cash flow sensitivity of underinvestment firms, while this relationship is described by a crescent S-shaped function for overinvestment firms. Our results also evidence that negative entrenchment effects of the largest ultimate shareholder make firms more dependent of internal funds than the high costs of external resources caused by asymmetric information in capital market. Keyword: investment-cash flow sensitivity, ownership and control, asymmetric information, agency costs of free cash flow.
Using Manifold Embedding for Automatic Threat Detection: An Alternative Machine Learning Approach

This paper presents an approach to automatic threat detection in X-ray imagery based on the combination of manifold embedding and a specialized classiﬁcation strategy to identify a wide range of ﬁrearm threats in imagery captured in operational settings and in challenging simulated settings which closely reﬂected operational conditions. The results show that this approach is successful in reducing the amount of data needed to produce a ﬂexible classiﬁcation system by two orders of magnitude if compared to most state-of-the-art deep learning systems used for object recognition. The work also offers useful indications to the amount of data required for such an alternative machine learning approach. It also shows an enhanced algorithmic architecture for the fusion of very different classiﬁers, so that a generic and ﬂexible system may be adapted to varied operational environments.
REVOLVING CREDIT: SHROUDED BY CONSTRUCTION

Creditors may find it optimal to not compete on price if consumers have difficulty translating credit price disclosures into true cost obligations. This paper presents empirical evidence combining newly compiled historical credit price data from mail-order catalogs and an experiment in an online labor market to show that this has indeed occurred with the emergence of revolving credit instruments, such as credit cards, whose primary price disclosure is an interest rate. I find that: 1) even when in plain sight of the consumer, interest rates do not sufficiently communicate cost obligations of revolving credit which leads to non-optimal borrowing and purchasing, 2) the credit instruments that were prevalent historically prior to the emergence of revolving credit are significantly better at communicating costs, and 3) credit issuers quickly adopted the innovation of revolving credit and subsequently followed pricing behavior that when contrasted with prior pricing behavior is consistent with their operating within a "shrouded equilibrium. " These findings provide empirical support for current theories on shrouding and suggest that effective policies to counter overconsumption and non-competitive pricing would need to increase salience of revolving credit costs prior to the purchasing decision through information other than interest rates.
Sleep Disturbances in Anorexia Nervosa: How Can They Be Explained?

Patients with anorexia nervosa (AN) frequently complain of insomnia and poor sleep quality. Some studies report changes in sleep self-reports and in several polysomnography parameters. These studies suggest that patients with AN and concomitant sleep disturbances have a poorer quality of life, are more predisposed to the appearance of comorbidities and have a poor prognosis of AN. The presence of sleep problems appears to influence the course and prognosis of AN. This article intends to briefly discuss the possible impact of sleep disturbances in AN and describe potential pathophysiological mechanisms involved.
A Pre-Trained Vs Fine-Tuning Methodology in Transfer Learning

Transfer learning from a pre-trained and fine-tuning methodology has been utilized for the image classification. In this paper, we classify images of cats and dogs. It is much faster and easier than training from scratch using a pre-trained network with transfer learning. This saved network was trained previously on a huge dataset and known as a pre-trained model. The pre-trained model can be used in two ways, either it is used in the same way or it utilizes transfer learning approach to adapt this pre-trained network to a specific goal. Since the idea for image classification using transfer learning is that it is trained on the general and large dataset and further this model will be efficiently worked on the visual perception task of the real world. In fine-tuning, instead of tuning with the weights of generic feature map of based model, it is tuned accordingly to the dataset. In this paper, we take benefit of these learned feature maps deprived of having to start from scratch by utilizing a deep learning technique on a huge dataset and analyze the various methodology. The experimental results show that fine-tuning methodology outperformed over the pre-trained with feature extraction on accuracy.
Current status of different detector technology in the searches of dark matter events

In this article, we review the possible candidates of dark matter and their proposed properties. We have focused on different methods used for the detection of the dark matter candidates such as, search of WIMPs at the accelerators, indirect and direct detection of WIMPs. We have highlighted the different detector technologies such as, charge collection after ionization, bubble formation in superheated liquid by charge particle, scintillation produced due to the incident radiation, cryogenic detection technique, noble liquid as detector material, time projection chamber, which are used by different experimental collaborations worldwide.