Miracle-dz/UniFAR-FTUs huggingface dataset:
Multivariable prediction model for predicting deaths in severe dengue cases

Background. Many predictive models have been developed to predict an outbreak, identify and stratify dengue but none has predicted death in severe dengue cases. To build a predictive model for deaths in severe dengue, a multicentre retrospective cohort study was conducted. Methods. Patients with severe dengue based on the World Health Organisation (WHO) 2009 classi�cation were studied. Demographic, clinical and laboratory data were collected at diagnosis of severe dengue. Penalised regression was used for variable selection and model-building. Ten-fold cross-validation with 1000 repeats were performed for internal validation. Results. A cohort of 786 severe dengue cases, including 35 deaths, was analysed. Our model that predicts death in severe dengue cases comprises eight independent predictors: persistent diarrhoea, body mass index, respiratory rate, platelet count, aspartate transaminase, serum bicarbonate, serum lactate and serum albumin. The area under the receiver operating characteristic curve is 89·6% with a sensitivity of 99·6%, speci�city of 23·6%, positive predictive value of 96·6%, negative predictive value of 71·1%, positive likelihood ratio 1·45 and negative likelihood ratio 0·01. We also found that the proportion of patients that were in the febrile phase at diagnosis of severe dengue for the overall cohort, decompensated and compensated shock were 74·3%, 73% and 75·4%, respectively. Conclusions. We developed a high-performance dengue death prediction model comprising clinical and laboratory data, and deployed an open-access web-based tool (www.saifulsafuan.com/REPROSED2017E2) for any centre to utilise for local validation. We additionally found that a large majority of patients developed severe dengue during the febrile phase.
Pragmatic Analysis of Diffusion in Computer Networks

Social networks is a content transportation medium, that has become more popular than the conventional fax and email system in the current world even shadowing the online messengers. With social websites like Facebook, Twitter etc., one can spread any type of information whether it be text, picture or video. Information of even an enormous size can spread like an epidemic on social networks. The researchers are intrigued by the interesting behaviors such networks are exhibiting and are delving in these types of networks. Content diffusion in computer networks is among trusted networks, just like information sharing on social websites where you are only allowed to share / view / comment only among trusted members. Among trusted networks one can spread information to achieve a diversity of tasks like marketing products or diffusion of job vacancies through pop-ups. On the other hand there can also be a malware that can utilize the same network and infect the trusted network. With the help of study of diffusion one can predict how to benefit from spreading of information in a network. Our interest in this paper is to study influence which is amongst the origins of diffusion for information spreading in a network. We have analyzed three real computer networks and compared them with artificially generated complex networks of random and scale free equivalent to each of them. Our experiments are based simultaneously on the concepts of Linear Threshold and Independent Cascade Model. We have used five different methods / metrics of selecting initial seed nodes and then calculated influence for each of them. Our experiments also include comparing of the metrics on each of the real networks and its corresponding random and scale free networks. Our experiments not only show that small amount of initial seed can infect maximum network but also that some metrics have same effect on equivalent networks while some donot.
./trilaterate: A Fabrication Pipeline to Design and 3D Print Hover-, Touch-, and Force-Sensitive Objects

Hover, touch, and force are promising input modalities that get increasingly integrated into screens and everyday objects. However, these interactions are often limited to flat surfaces and the integration of suitable sensors is time-consuming and costly. To alleviate these limitations, we contribute Trilaterate: A fabrication pipeline to 3D print custom objects that detect the 3D position of a finger hovering, touching, or forcing them by combining multiple capacitance measurements via capacitive trilateration. Trilaterate places and routes actively-shielded sensors inside the object and operates on consumer-level 3D printers. We present technical evaluations and example applications that validate and demonstrate the wide applicability of Trilaterate.
Early detection of heterogeneous disaster events using social media

This article addresses the problem of detecting crisis‐related messages on social media, in order to improve the situational awareness of emergency services. Previous work focused on developing machine‐learning classifiers restricted to specific disasters, such as storms or wildfires. We investigate for the first time methods to detect such messages where the type of the crisis is not known in advance, that is, the data are highly heterogeneous. Data heterogeneity causes significant difficulties for learning algorithms to generalize and accurately label incoming data. Our main contributions are as follows. First, we evaluate the extent of this problem in the context of disaster management, finding that the performance of traditional learners drops by up to 40% when trained and tested on heterogeneous data vis‐á‐vis homogeneous data. Then, in order to overcome data heterogeneity, we propose a new ensemble learning method, and found this to perform on a par with the Gradient Boosting and AdaBoost ensemble learners. The methods are studied on a benchmark data set comprising 26 disaster events and four classification problems: detection of relevant messages, informative messages, eyewitness reports, and topical classification of messages. Finally, in a case study, we evaluate the proposed methods on a real‐world data set to assess its practical value.
Determinants of health-related quality of life in colon cancer patients include stoma and smoking habits, but not type of surgery

Background: Health-related quality of life (HRQoL) has gained increased attention in cancer care. Studies have shown that poor QoL might worsen the cancer related prognosis. The aim of this study was to investigate HRQoL in patients with colon cancer and to compare data with reference values from the general population in Sweden at diagnosis (baseline) and at six months of follow-up. Methods : This was a prospective population-based study of colon cancer patients from Västmanland County, Sweden, included between March 2012 and September 2016. HRQoL was measured using the cancer-specific EORTC QLQ-C30 questionnaire. Data on HRQoL was compared with Swedish population reference values. Multiple linear regression analysis adjusted for age, sex, body mass index (BMI), American Society of Anaesthesiology (ASA) physical status classification, emergency/elective surgery, and resection with/without a stoma and tumour stage (TNM), was used. Results : A total of 67% (376/561) of all incident colon cancer patients (196 [52.1%] females) were included. Mean (range) age was 73 (30-96) years. The univariate analysis showed that patients with colon cancer had worse QoL (8/15 parameters) compared with a Swedish reference population both at baseline and at 6 months follow-up. Furthermore, linear regression analysis showed that patients with more comorbidity (ASA 3 and 4), smokers and patients planned to be operated on with a stoma, were at higher risks for poor QoL than the other included patients. Conclusions : The reported determinants of HRQoL may be used to identify risk groups and enable individualized care for patients that need more support from health care.
Localization of computer-mediated communication and corporate impression on online communities

Purpose The purpose of this paper is to investigate the importance of localizing online communities (OCs) and examines how OC members form impressions of organizations that use OCs in their communication activities. A conceptual framework and measurement scale are developed that consist of complex latent constructs. Design/methodology/approach A sequential multi-method approach is adopted with both qualitative and quantitative investigations. Using Structural equation modeling, the research refines and validates the measurement scales of impression formation in OCs. Findings Findings reveal that comprehensive messages have a direct effect on the impressions that an OC member forms. In particular, social context cues are an important predictor of online community corporate impression (OCCIP). Source credibility, affiliation, characteristics and interpersonal communication are all critical to OCCIP, which in turn, influence members’ attitudes toward the company and the intention to use it again. Surprisingly, relevance, timeliness, accuracy and perceived similarity did not have any significant effect on the corporate impression. Originality/value Three contributions are offered: First, the study provides reliable scales for measuring OCCIP. Second, support is given to the conceptual model that links OCCIP to a set of consequences, namely, attitudes toward the company, intention to use the company, and word-of-mouth. Finally, the study is conducted across two different and unique types of OC contexts, stipulating further insights into the localization of OCs.
Knowledge, Beliefs and Attitudes Towards Dementia and Dementia Risk Reduction Among Descendants of People with Dementia: A Qualitative Study Using Focus Group Discussions

Background Individuals with a parental family history of dementia have an increased risk of developing dementia because they share their genes as well as their psychosocial behaviour. Due to this increased risk and their experience with dementia, they may be particularly eager to receive information regarding dementia risk reduction (DRR). This study evaluated the knowledge, beliefs and attitudes towards dementia and DRR among descendants of people with dementia.Method Using a semi-structured topic guide, three focus group discussions were conducted consisting of 12 female (80%) and 3 male (20%) descendants of people with dementia with a mean age of 48.8 ± 12.0 years. Focus group discussions were audio recorded and transcribed. Each transcript was analysed thoroughly, and where appropriate, a code was generated and assigned by two researchers independently. Then, similar codes were grouped together and categorized into themes.Results The items in the topic guide could only be addressed after participants had been given the opportunity to share their experiences of having a parent with dementia. Participants were unaware or uncertain about the possibility of reducing the risk of developing dementia and therefore hesitant to assess their dementia risk without treatment options in sight. Moreover, participants indicated that their general practitioner only gave some information on heritability, not on DRR. Although participants identified a large number of modifiable risk factors as a group during the group discussions, they were eager to receive more information on dementia and DRR. In the end, participants adopted a more positive attitude towards a DRR program and provided suggestions for the development of future DRR programs.Conclusions Although the research aim was to evaluate the knowledge, beliefs and attitudes towards dementia and DRR, sharing experiences of having a parent with dementia seemed a prerequisite for considering participants’ own risk of developing dementia and participating in a DRR program. Knowledge of dementia and DRR was limited. Due to unawareness of the possibility of reducing dementia risk, participants were hesitant about assessing their dementia risk. Group discussions positively changed the perception of dementia risk assessment and participants’ willingness to participate in a DRR program.
Morphological and molecular characterization of Croatian carob tree (Ceratonia siliqua L.) germplasm

Recommended Citation BOLARIC, SNJEZANA; MÜLLER, IVNA DRAGOJEVIC; VOKURKA, ALES; CEPO, DUBRAVKA VITALI; RUSCIC, MIRKO; SRECEC, SINISA; and KREMER, DARIO (2021) "Morphological and molecular characterization of Croatian carob tree(Ceratonia siliqua L.) germplasm," Turkish Journal of Agriculture and Forestry: Vol. 45: No. 6, Article 11. https://doi.org/10.3906/tar-2107-24 Available at: https://journals.tubitak. gov.tr/agriculture/vol45/iss6/11
Digital Serializer Design for a SerDes Chip in 130nm CMOS Technology

The development of this project is derived from the effort of previous generations from the System on Chip Design Specialty Program at ITESO, who have pioneered the creation of a serializer-deserializer device for high-speed communications in CMOS technology, aiming towards a small and efficient device. The design flow and enhancements implemented within the digital serializer module of the SerDes system, consists of an 8b10b encoder followed by a parallel to serial converter that together reaches a maximum frequency of 239 MHz in a typical cmrf8sf (130 nm) technology manufacturing process, implemented with Cadence tools. The rtl and testbench were taken from the work of Efrain Arrambide, adding a register to store the current disparity value, and thus, enhance the code by adding primitive blocks to improve the behavior of the serializer module and the validation process, generating a summary for every run. The system on chip flow is followed by choosing the variables that best fit the design and a layout with no design violations is generated during the physical synthesis. The individual module layouts were completed successfully in terms of behavior and violations, while the integration of the mixed signal device showed errors that were not resolved in time for manufacturing.
The Effects of Emotions and Genders toward Creativity among Undergraduate Students of Universiti Pendidikan Sultan Idris

As Malaysia’s national curriculum appeared to promote creative subjects instead of enhanced by itself, this study aimed to study the effect of emotions and genders toward creativity among undergraduate student in Universiti Pendidikan Sultan Idris (UPSI). This study was conducted through experimental method. This between-subject experimental study was conducted by watching a short video and complete a set of questionnaire to the participants. A total of 32 participants with equal gender were participated in the experiment through convenience sampling. Instruments used were the PANAS Questionnaire and Alternative Uses Task (AUT). Two types of videos to give intended effect of positive and negative emotions were used. Manipulation check was conducted before the actual study to test the instruments. Research hypotheses were tested by the independent T-test analyses. Results showed that there was no significant difference between both emotions and genders respectively toward creativity. Lastly, thorough discussions on the effect of emotions and genders among these variables toward creativity were presented in this paper. Some implication, limitation and recommendation for future study were discussed.
Detection and classification of traffic objects using the environment digits

An overview of the architecture of the DetectNet neural network was conducted to study the model of detection and classification of traffic objects. In this case, the structure of the neural network and the format of the input data are considered. The modeling is done using the DIGITS environment. The quality of the model was tested on the image validation dataset KITTI. The results of studying the model of the neural network are presented. The results obtained compared with existing ones.
Scale-Free Cooperative Control of Inverter-Based Microgrids With General Time-Varying Communication Graphs

This paper presents a method for controlling the voltage of inverter-based Microgrids by proposing a new scale-free distributed cooperative controller. The main contribution of this paper is that the proposed distributed cooperative controller is scale-free where is independent of any information about the communication system and the number of distributed generators, as such it works for any Microgrids with any size. Moreover, the communication network is modeled by a general time-varying graph which enhances the resilience of the proposed protocol against communication link failure, data packet loss, and arbitrarily fast plug and play operation in the presence of arbitrarily finite communication delays as the protocol does not require the knowledge of the upper bound on the delay. The stability analysis of the proposed protocol is provided. The proposed method is simulated on the CIGRE medium voltage Microgrid test system. The simulation results demonstrate the feasibility of the proposed scale-free distributed nonlinear protocol for regulating voltage of Microgrids in the presence of communication failures, data packet loss, noise, and degradation.
CO2 Reduction to Propanol by Copper Foams: A Pre- and Post-Catalysis Study

The utilization of carbon dioxide is a major incentive for the growing field of carbon capture. Carbon dioxide could be an abundant building block to generate higher value products. Herein, we describe the use of porous copper electrodes to catalyze the reduction of carbon dioxide into higher value products such as ethylene, ethanol and, notably, propanol. For n-propanol production, faradaic efficiencies reach 4.93% at -0.83 V vs RHE, with a geometric partial current density of -1.85 mA/cm2. We have documented the performance of the catalyst in both pristine and urea-modified foams pre- and post-electrolysis. Before electrolysis, the copper electrode consisted of a mixture of cuboctahedra and dendrites. After 35-minute electrolysis, the cuboctahedra and dendrites have undergone structural rearrangement. Changes in the interaction of urea with the catalyst surface have also been observed. These transformations were characterized ex-situ using scanning electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. We found that alterations in the morphology, crystallinity, and surface composition of the catalyst led to the deactivation of the copper foams.
International Journal of Information Systems in the Service Sector

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Current Distribution Estimation of Parallel-Connected Batteries for Inconsistency Diagnosis Using Long Short-Term Memory Networks

In electric vehicle applications, lithium-ion batteries are usually used in parallel connections to meet the power and energy requirements. However, the impedance and capacity inconsistencies among the parallel-connected batteries (P-LiBs) can lead to uneven current distribution, resulting in accelerated aging and safety issues. Since it is impractical to equip current sensors for all battery cells, this work aims to estimate the uneven current distribution without additional hardware which can be used for inconsistency diagnosis. The characteristics of P-LiBs under inconsistency are investigated by experimental study, the current distribution, and voltage curve of P-LiBs that are found to exhibit different features under various inconsistency conditions. Consequently, a recurrent neural network (RNN) with long short term memory (LSTM) is adopted to estimate the current distribution using only the terminal voltage and total current information. The proposed method is validated with two parallel-connected cells and the experimental results indicate a good estimation accuracy in both inconsistent impedance and aging conditions. Furthermore, in the case of more cells in parallel, the trend and abnormal rise of branch currents are still accurately tracked in three- and four-parallel connection situations. Based on the estimated current distribution, the inconsistency faults within P-LiBs can be efficiently diagnosed.
HetNets With Range Expansion: Local Delay and Energy Efficiency Optimization

In this paper, we explore the different per-user bandwidths available for each tier of heterogeneous networks (HetNets) and the corresponding downlink range expansion (RE, a key measure to boost small cell association). Based on the practical case of tier-specific path loss exponents, we derive the local delay of HetNets under the random discontinuous transmission scheme (DTX, employed to manage the interference and reduce energy consumption). Using such a new expression for local delay, we then analyze the corresponding energy efficiency (EE). These delay and EE expressions reveal that there exists an optimal value for both the RE bias factor and for the DTX mute probability. A closed-form optimum solution for the RE bias factor is also derived for the low-rate regime.
Effect of Chalk Dust Exposure on PEFR and CAT in School Teachers

In teachers, occupational exposure to chalk dust is very common. Classrooms contain of fine particulate matter that source from chalk dust. To further evaluate and study the symptoms of respiratory illness in school teachers, the present study was conducted in order to evaluate individual’s degree of obstruction using the PEFR, and its impact on their overall health, using COPD assessment test. This comparative study was conducted in 40 School teachers and 40 normal healthy individuals. The data for this study was collected using mini Bell’s PEFR device and the COPD Assessment test (CAT). An analysis of the data showed that the mean CAT score of group A (teachers) was significantly higher (p=0.001) than group B (normal individuals). The mean PEFR for group B was higher than group A, although the difference was not statistically significant. Hence, the study concluded that respiratory symptoms significantly impacted the health of school teachers. They also showed signs of airway obstruction as compared to normal individuals.
Methods for benchmarking photolithography simulators: part II

Numerical simulation has become an indispensable tool for the design and optimization of photolithographic processes. Because the semiconductor industry now relies heavily on these tools, it is necessary to be able to benchmark their accuracy - as feature sizes continue to shrink, the numerical error in these simulators must decrease as well. In a previous paper, we proposed benchmarks for aerial image calculation that were drawn from the optics literature. Because these benchmarks were closed-form solutions, we could use these results as an absolute standard for determining the numerical accuracy of an aerial image calculation. In the current study, we continue this effort by presenting closed-form solutions that can serve as benchmarks for the resist response to the projection optics. Benchmarks are proposed for film stack reflectivity and image in resist. Specific results will be presented for PROLITH.
A Security Protocol Model of Internet of Things for Resisting Known Plaintext Attack

Based on the current research status of security problems in the Internet of things and the communication characteristics of the internet of things, an Internet of things security protocol model that can resist known plaintext attacks was proposed. It realizes identity authentication, key distribution and data encryption in the process of information interaction. By using Casper and FDR tool to model and formalize the security protocol proposed, the security of this protocol was proved. The performance of the protocol was analyzed by comparing it with other IoT security protocols and calculating the expected network communication overhead.