Miracle-dz/UniFAR-FTUs huggingface dataset:
A network-based analysis of genes related to comorbidities in diabetes.

Network medicine helps to shed light insight many chronic diseases by offering useful information about mechanistic information from omic data sets. Type 2 diabetes mellitus (T2DM) is one of the major challenges in medical research. it has been demonstrated that the odds of comorbidities is different considering age and sex of patients. Therefore the use of a framework such as a system and network approach may be useful to shed light into uncertainties related to sex, age effects and comorbidity. We first selected from T2Dico database the list of genes related to comorbidities. Then we first extracted networks of proteins connecting them. In parallel we analysed the pattern of expression of them considering both age and sex as factors, stored into the GTEx database. Preliminary results showed the action of few genes and the biological validation is currently carried out.
Exploring the stationarity of Australian temperature, precipitation and pan evaporation records over the last century

Australia has experienced regional climate trends over recent decades with consequences for agriculture and water management. We investigate the statistical significance of these trends at annual and seasonal scales using the concept of stationarity. Using long-term high quality regional-scale observations of temperature, precipitation and pan evaporation (a measure of atmospheric evaporative demand), we find that despite highly significant increases in temperature that are non-stationary, few regions of Australia have experienced annual or seasonal changes in precipitation or pan evaporation that are outside the range of observed variability over the last century. Despite a common assumption of increasing water demand under a warming climate, atmospheric evaporative demand (as measured by pan evaporation) largely remains unchanged. This is because evaporative demand depends strongly on factors other than temperature. Similarly, seasonal and annual precipitation over the last century is found to be stationary in most (but not all) regions. These findings suggest that the Australian precipitation has largely remained within the bounds of observed variability to date and emphasises the need to better account for variability in water resource management.
Marriage Timing and Forward Contracts in Marriage

We study how contractual incompleteness affects marriage contracts, including premarital investments in human capital, age of marriage, and the timing of payments. We formalise different solutions to the contractual problem and document their use across societies and at different points in history. The most common form of marriage arrangement today is one where human capital investments precede the marriage agreement. However, two other forms of contractual arrangements have also been prevalent in the past: (i) transfer of the bride to the groom's family prior to human capital investments (e.g. pre-pubescent marriages); (ii) a forward contract specifies investments to be made in the bride before her transfer to the groom's family (e.g. cradle betrothal). Each alternative suffers from a form of inefficiency (due, respectively, to search costs, agency problems in childrearing, and underinvestment due to the classical hold-up problem). The model generates predictions regarding the contractual form adopted as a function of the prevailing production technology, population density, and credit constraints. We argue that a theory of marriages that allows contractual form to be endogenous provide insights about the impact of development policies that are missed when the contractual form is taken as given.
Modeling customer satisfaction and revisit intention in Bangladeshi dining restaurants

PurposeThe purpose of this study is to provide an insight into the crucial antecedents of customer satisfaction and revisit intention in the context of dining restaurants in a holistic approach, taking Bangladesh as a unit of analysis.Design/methodology/approachThe research design was cross-sectional. Data were collected from 30 dining restaurants in Dhaka city, Bangladesh. The proposed model was tested using partial least square structural equation modeling with a sample size of 600 respondents.FindingsThe antecedents of customer satisfaction (i.e. service quality, food quality, atmospherics, other customers and perceived value/price) were found to have significant positive effects on customer satisfaction. Customer satisfaction and restaurant reputation were found to have significant positive effects on revisit intention, while variety seeking tendency was found to have a significant negative effect on revisit intention. Trust was found to partially mediate the customer satisfaction-revisit intention and restaurant reputation-revisit intention relationships.Originality/valueThis study is among the first to provide a holistic approach toward the crucial antecedents of customer satisfaction (i.e. service quality, food quality, atmospherics, other customers and perceived value) and revisit intention (i.e. customer satisfaction, variety seeking tendency, trust and restaurant reputation) in one structural equation model, and investigated their interrelationships in the context of dining restaurants. To the authors’ knowledge, this is the first study that has investigated the mediating role of trust between the customer satisfaction-revisit intention and restaurant reputation-revisit intention relationships in the context of dining restaurants. From a market-specific context, this the first study to investigate and link the examined variables in the context of Bangladeshi dining restaurants.
Ethics: What is the Research Scenario in the LARS/SBR/WRE?

Robotics is a recurring and widely present theme in computational ethics. Despite specific problems or pessimistic views about robots and robotics, such as security problems or the risk of human unemployment, there are several advantages, improvements, and positive aspects. The Latin American Robotics Symposium (LARS) is the largest conference dedicated to robotics in Latin America, held jointly with the Brazilian Robotics Symposium (SBR) and the Workshop of Robotics in Education (WRE). The focus is to advance the robotic academic-scientific research and aggregate the robotic community members, strengthening this network. In this paper, we present a broad and in-depth overview of ethical aspects through LARS/SBR/WRE publications to answer this research question: how has ethics been addressed in LARS, SBR, and WRE papers published in the last decade (2012-2021)? We followed a widely used Systematic Literature Review method to ensure methodological rigor. After analyzing the results, we noticed a low occurrence of ethical aspects, but the reflections are fruitful and rich in the publications where they occur. There are plenty of research opportunities involving ethics and robotics, positioning LARS/SBR/WRE at the forefront of this discussion.
Efficacy and Safety of Geochangmanryeung-dan and Acupuncture on Patient with Spinal Stenosis Treated by Epidural Steroid Injection: a Study Protocol for a Randomized Controlled Pilot Trial

Objectives : This study was designed to obtain basic data for a further large-scale trial as evaluating the efficacy and safety of Geochangmanryeung-dan(GMD) and acupuncture on patient with spinal stenosis treated by epidural steroid injection. Methods: The study is a randomized controlled pilot clinical trial, conducted over 8 weeks. Twenty participants will be recruited and randomly allocated to 2 groups: an experimental(GMD and acupuncture with epidural steroid injection) group and a control(only epidural steroid injection) group. The epidural steroid injection will be administered once per 2 weeks for 6 weeks(3 times in total). GMD will be administered as a dose of 5 pills, 3 times per day, for 6 weeks. Acupuncture will be performed 2 times per week for 6 weeks(12 times in total). The primary outcome will be measured by visual analogue scale and self-rated walking distance. The secondary outcome will be measured by PainVision, short-form McGill Pain Questionnaire, and Oswestry Disability Index. Both primary and secondary outcomes will be measured at baseline, 2, 4, 6, and 8 weeks. The last assessment(at 8 weeks) will be performed 2 weeks after treatment cessation. Conclusions : This clinical trial, as the pilot study for a future large-scale trial, will provide clinical information for evaluating the efficacy and safety of GMD and acupuncture treatment in combination with epidural steroid injection for the treatment of spinal stenosis.
Prospect of Analyzing Integrated Circuits Based on Dataset with Synthesis Results

When designing blocks for integrated circuits, it is crucial to understand whether the module in question meets set constraints. Area and timing are important parameters which are being obtained after synthesizing the circuit with specialized tools. However, this process can be too time consuming. In this paper we present an overview of methods, which can be used to determine area and timing with a prepared dataset. Bilinear interpolation, approximation and deep neural networks are being used for this task. The results show that though the first two methods can be used in special cases, the machine learning approach is more flexible and can be effectively implemented for integrated circuit analysis.
Superposition of Time-dependent Data for Accelerated Aging of Nuclear Power Plant Cables and Its Validity

A cable operated in a nuclear power plant (NPP) was removed to examine its degradation degree. Artificial aging was given to a similar new cable insulated with the same material so that we could simulate the degradation that the removed cable had suffered in three different manners by changing the dose rate and period of gamma-ray irradiation. For these cable samples removed or artificially aged, instrumental analyses were conducted. As a result, the validity of a method called “superposition of time-dependent data” used to give the artificial aging to simulate the aging of cables in a NPP has been confirmed.
Topological network properties of the European football loan system

ABSTRACT Research question: Following a network perspective, we present football's European loan system as an economic network and aim to answer the following questions; (i) what is the structure of the network? and, (ii) what are the topological properties of the network? Research methods: Using data on the top-5 European leagues in European football 8139 loan transactions between 31 December 2009 and 22 December 2017 were analysed using social network analysis. Results and findings: The results show that the loan system is embedded in ongoing structural relationships across Europe, more so in the Italian Serie A than other European leagues investigated. Additionally, our findings indicate that several elite clubs are extracting value from the loan system, while others are value creators. Implications: The implications of this research are fourfold: recommendations for executive-level professionals in the football industry and how to maximise the structure of the system; considerations for UEFA and FIFA policy around regulations applied to loan systems; application of economic network theory to the trading (loan) system in European football; and recommendations for future academic research.
The extreme risk spillovers between the US and China’s agricultural commodity futures markets

In this study, we investigate the downside and upside risk spillover effects between the same kind of agricultural futures in the Chinese and US markets, taking the value-at-risk (VaR) and conditional value-at-risk (CVaR) as a risk measure, characterized and computed using copula-GARCH approach. We find evidence of a significant positive dependence between the US and Chinese agricultural commodity futures markets. And the empirical results also show that the existence of downside and upside risk spillover effects between variables, especially significant during financial turmoil periods. Market regulators and traders of agricultural futures will benefit by identifying tail dependence and extreme risk spillovers.
Compliance costs and comparability benefits of cross-listing

Purpose The purpose of this paper is to examine two channels through which accounting standard differences could affect cross-listing: compliance costs and/or comparability benefits. Design/methodology/approach The authors use two settings to disentangle the two channels. First, financial reporting requirements are more stringent for cross-listings via direct listings than cross-listings via depositary receipts; as a result, the effect of compliance costs (if any) would be manifested differently in the two venues of cross-listings. Second, some host countries allow foreign firms to report under International Financial Reporting Standards (IFRS) without mandating IFRS for domestic firms; compared to host countries that mandate IFRS for both domestic and foreign firms, these IFRS-permitting countries provide a setting to test the importance of comparability benefits while holding constant compliance costs. Findings The authors find that prior to IFRS adoption, direct listings decrease with accounting standards differences between two countries while depositary receipts increase with such differences, consistent with the costs of complying with host country’s accounting standards affecting firms’ cross-listing decisions. After the harmonization of accounting standards, the authors find that IFRS-mandating host countries gain cross-listings from other IFRS-mandating jurisdictions, while IFRS-permitting countries do not experience such gains. These combined results suggest that accounting related compliance costs and comparability benefits both influence cross-listing decisions. Originality/value The paper employs unique settings that enable an in-depth examination of the role of compliance costs vs that of comparability benefits on cross-listing decisions. The settings employed by the authors allow them to disentangle the two channels and provide an important insight that accounting standard-related compliance costs and comparability benefits both affect cross-listing decisions.
Prediction Models for Epilepsy Detection on the EEG Signal

Epilepsy is a neurological illness characterized by abnormal brain activity, resulting in seizures or episodes of odd behavior, feelings, and in some cases, loss of awareness. In this work, we propose a comparison between three deep learning models: Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) and bidirectional LSTM for epileptic seizure detection using EEG data which is the most common technique used for Epilepsy diagnosis. The objective of this work is to define the most suitable model for this sensitive task and to reach the highest possible accuracy. To evaluate the performance of the proposed methods, many experiments are conducted to study the effect of some parameters and using two categorical combinations of an EEG dataset. As a result, we reached a prediction accuracy of 90.26% with CNN, 86.17% with LSTM but the Bi-LSTM model consistently outperformed the other models reaching more than 98% accuracy. Finally, these results demonstrate the possibility of detecting the epileptic seizures while maintaining model interpretability, which may contribute to a better understanding of brain dynamics and enhance predictive performances.
The Role of Exporters’ Emotional Intelligence in Building Foreign Customer Relationships

Despite the critical importance of emotional intelligence in effectively interacting with other people, its role has been overlooked in scholarly research on cross-border interorganizational relationships. Drawing on emotion regulation theory, the authors propose a model that conceptualizes links among exporters’ emotional intelligence, key behavioral dimensions characterizing the atmosphere of the relationship with import buyers, and the resulting relational performance. They test the model with data collected from 262 Greek exporters using structural equation modeling. The results indicate that higher levels of exporter emotional intelligence enhance communication and social bonding with the importer while diminishing distance and conflict in their working relationship. Relational performance is positively influenced by communication and social bonding but negatively affected by distance and conflict. The results also reveal the moderating effect of both opportunism and interpartner incompatibility on the association between the exporter’s emotional intelligence and the behavioral atmosphere of the relationship with import buyers.
Radiation Pattern of a Radially Arranged Array in Relation with the Number of Linear Arrays

The radiation of an array antenna that is composed of linear arrays in radial arrangement is analyzed changing the number of the linear arrays. It is verified that the characteristics are greatly dependent on the number of linear arrays, and is well illustrated with a two-dimensional diagram of contour. The angular limitation to give the sinc pattern are clarified. Outside the limitation, there exist unwanted side lobes that are featured with high level and wide beam width.
Application of YOLOv5 and MASK R-CNN for diurnal activity monitoring of freshwater fish

Real-time monitoring of aquatic environment such as fish is an important task for a deeper understanding of aquatic ecosystems. While underwater monitoring has been studied intensively, it is still challenging to monitor target ecosystems during night-time. In this study, we aim to develop an image processing pipeline to monitor small freshwater fish in day and night. For this purpose, we used instance segmentation and object detection as an image processing technique specifically for detecting fish individuals in an image. We collected images of our target fish, Nipponocypris temminckii in a spring-fed stream in Tokyo. Images were taken using hand-held digital cameras during the daytime for model training and validation. We then applied data augmentation for model training by adjusting brightness and sharpness, reducing image resolution, and copy-paste augmentation, from which six data sets were prepared by additively combining these methods. Also, in the laboratory aquarium experiment, time-lapse images of the target fish were taken from two directions. The images taken from the eastern side were used as test images, while the images taken from the northern side were used as training images. Half of them were taken in the evening using an infrared camera. We first trained a Mask R-CNN on each of the training data sets and applied it to the test images to verify the accuracy of fish detection and to compare the applicability of the data augmentation methods employed. Then, we compared the framework by training YOLOv5 on the dataset that showed the highest accuracy in training the Mask R-CNN and images acquired in the experiment. Results showed that the combination of many data augmentation methods improved the accuracy of fish detection and allowed for fish detection with infrared images. In particular, we found that the copy-paste method improves the detection accuracy on infrared images taken under a dark condition.
The Effect of Compensation Caps on Risk-Taking

Using an experiment, we investigate the joint effects of compensation caps and formal justification requirements on risk-taking. Compensation caps restrict the earnings potential of decision-makers and have been implemented to influence risk-taking behavior, especially after the financial crisis. Rational choice theory predicts that caps should restrict only risk-seeking decision-makers from taking undesired risk and not affect risk-averse decision-makers. Based on the compromise effect, however, we predict that compensation caps will also affect risk-averse decision-makers. Moreover, we posit that the effect of compensation caps on risk-averse decision-makers is stronger in the presence of high justification pressure. Our results support both hypotheses and indicate that compensation caps have unintended consequences. In particular, risk-averse decision-makers also take less risk when their compensation is capped, especially in combination with justification requirements, which are another frequently used instrument to steer risk-taking. The result might be dysfunctionally low levels of risk-taking for exploiting entrepreneurial opportunities.
Design of Compact Bandpass Filter with Stub-Loaded to The Closed Loop Resonator

In this paper, a compact 3-order Band-pass filter (BPF) is proposed using a resonator that adds stub-loaded to the closed loop resonator. In consideration of coupled with 50$\Omega$ feeding line, the first and last resonator of $\lambda_{0}/4$ is folded type. The proposed filter is designed and fabricated with a fractional bandwidth of 8% at 1GHz center frequency. As compared to the area of the conventional interdigital BPF, a decrease of 50.04% is verified. Experimental results have shown good agreement with simulated ones.
Multiple anthropogenic drivers behind upward trends in organic carbon concentrations in boreal rivers

Increases of riverine organic carbon concentrations have been observed across the northern hemisphere over the past few decades. These increases are the result of multiple environmental drivers, but the relative importance of the drivers is still unclear. We analyzed a dataset of >10 000 observations of riverine total organic carbon (TOC) concentrations and associated water chemistry and hydrological observations from 1993 to 2017. The observations span a ∼600 km north–south gradient from 30 individual river systems in Finland. Our data show significantly increasing TOC concentrations in 25 out of 30 systems, with an average increase from 12.0 to 15.1 mg l−1. The observed increase in riverine TOC concentrations led to an increase of 0.28 Mt in annual TOC load to the Baltic Sea from 1993 level to 2017 level. We analyzed the role of three putative environmental drivers of the observed TOC trends. Multiple regression analysis revealed that the most common driver was discharge, which alone explained TOC increases in 13 rivers, whereas pH and temperature were less important drivers (sole predictor in one and zero rivers, respectively). Different permutations of these three drivers were also found to be significant; the combination of discharge and pH being the most common (4 rivers). Land use was not in general linked with trends in TOC, except for the proportion of ditched land in the catchment, which was significantly correlated with increases in TOC concentration. Land use showed significant relationships with trends in discharge and pH. We also found that catchment characteristics are regulating the extent of these regional or global environmental changes causing the upward trends of riverine organic carbon.