Miracle-dz/UniFAR-FTUs huggingface dataset:
FedGroup: Efficient Federated Learning via Decomposed Similarity-Based Clustering

Federated Learning (FL) enables the multiple participating devices to collaboratively contribute to a global neural network model while keeping the training data locally. Unlike the centralized training setting, the non-IID and imbalanced (statistical heterogeneity) training data of FL is distributed in the federated network, which will increase the divergences between the local models and the global model, further degrading performance. In this paper, we propose a novel clustered federated learning (CFL) framework FedGroup, in which we 1) group the training of clients based on the similarities between the clients’ optimization directions for high training performance; 2) construct a new data-driven distance measure to improve the efficiency of the client clustering procedure. 3) implement a newcomer device cold start mechanism based on the auxiliary global model for framework scalability and practicality.FedGroup can achieve improvements by dividing joint optimization into groups of sub-optimization and can be combined with FL optimizer FedProx. The convergence and complexity are analyzed to demonstrate the efficiency of our proposed framework. We also evaluate FedGroup and FedGrouProx (combined with FedProx) on several open datasets and made comparisons with related CFL frameworks. The results show that FedGroup can significantly improve absolute test accuracy by +14.1% on FEMNIST compared to FedAvg, +3.4% on Sentiment140 compared to FedProx, +6.9% on MNIST compared to FeSEM.
SEISMIC HAZARD ANALYSIS OF THE ACROPOLIS OF ATHENS AND SEISMIC ANALYSIS OF PROPYLAEA COLONNADE

The paper presents a preliminary study of the seismic hazard of the Acropolis of Athens, a World Heritage Site since 1987, and the seismic response of some of its classical monuments. The objectives are threefold. The first is to perform both probabilistic and deterministic seismic hazard analysis simulating the expected strong ground motion from eight earthquake scenarios that are associated to large faults in the proximity of the Acropolis comparing the results with the existing relevant studies. The results of the analysis proved that the expected seismic actions may vary from 0.14g to 0.33g for 475 years return period. The second objective is to analyze available strong ground motion records from few recent earthquakes, recorded by the high-quality accelerometer array installed in Acropolis, operated by the Institute of Geodynamics, National Observatory of Athens in collaboration with the Acropolis Restoration Service. The analysis of two events proved that the hill of Acropolis is not shaking as a rigid body in the two main directions and that the field earthquakes might generate strong long period shaking amplitudes in the longer dimension. The final goal is to study the seismic response of few selected world-class monuments of the Acropolis Propylaea. A free-standing multi-drum column and a colonnade consisting of three columns coupled with an architrave were studied applying 3D full dynamic time history analyses in ABAQUS. The model used has been well validated with experimental data from recent shaking table tests on multi-drum columns and proved to efficiently simulate complex phenomena at the interfaces, including sliding and/or rocking. The main results of the analysis proved that the monuments that have been studied are safe for seismic excitations even larger than 0.33g.
ACCEPTANCE OF OTT VIDEO STREAMING PLATFORMS IN INDIA DURING COVID -19: EXTENDING UTAUT2 WITH CONTENT AVAILABILITY

The paper aims at identifying factors that stimulates the customers to adopt and use OTT video streaming platforms in India by applying unified theory of acceptance and use of technology 2 (UTAUT2) model. The study has also attempted to check the moderation effect of age, gender, experience. The study uses a questionnaire to gather the primary data of 277 users of OTT video streaming platforms of India as respondents. The data was examined using SmartPLS 3.3. 2 software. The key drivers of adopting and using OTT video streaming platforms are performance expectancy, price value, habit and content availability. The study approves the relevance of UTAUT2 model in the present context. The study also explains the moderating effect of gender, experience and age in UTAUT2 model constructs with respect to OTT video streaming platforms. The market of OTT platforms in India is growing tremendously and is projected to gain the momentum in coming years. Thus, it is imperious to comprehend the behavioral intention of consumers. The outcomes of the study will help the managers in comprehending and devising different strategies for consumers of OTT video streaming platforms. The study is first ever attempt to the best understanding of research to observe the acceptance of OTT video streaming apps using UTAUT2 model.
Investigation on Physicomechanical Properties and Constitutive Model of Tuff in Mila Mountain Tunnel under Dry and Saturated Conditions

Many tunnel engineering accidents are generally caused by water softening tuff of high porosity. Experimental and theoretical analytical methods, including rock ultrasonic testing, X-ray diffraction (XRD), microscopic observation, uniaxial compression test, and scanning electron microscope (SEM), are employed to analyze the physicomechanical properties of tuff in Mila Mountain tunnel under dry and saturated conditions. Then, the mechanism of tuff softening in water is explained. Finally, the statistical damage constitutive model of tuff is established. It was revealed that the tuff compositions were dominated by quartz and clay minerals accounting for more than 90%, and clay minerals, anhydrite, and pyrite were mainly soluble minerals. After being saturated with water, the soluble minerals in the tuff are dissolved, and the porosity and wave velocity are increased; however, the elastic modulus and peak strength are decreased, indicating that water softening was distinct. Water softening after saturation was due to the mineral compositions and microstructure characteristics of tuff in Mila Mountain tunnel; specifically, as the tuff characterized by high porosity was conductive to water absorption, the soluble minerals in the tuff were corroded and swelled by water, dissolving, loosening, and softening the tuff structure; then, its mechanical behavior was degraded. It was demonstrated by the experimental results consistent with theoretical results that the model can be employed to express the constitutive behavior of tuff in Mila Mountain tunnel under dry and saturation conditions. The findings provide insights into macroscale deterioration of tuffs and theoretical knowledge for the tunnel excavation and support of Mila Mountain tunnel.
Dynamics of Phosphorus and Organic Substrates in Anaerobic and Aerobic Phases of a Sequencing Batch Reactor

This paper describes a lab-scale experimentation carried out to study enhanced biological phosphate removal (EBPR) in a sequencing batch reactor (SBR). The synthetic feed used was based on peptone and glucose as organic substrate to simulate the readily biodegradable fraction of a municipal wastewater (Wentzel et al. , 1991). The experimental work was divided into two runs, each characterized by different operating conditions. The phosphorus removal efficiency was considerably higher in the absence of competition for organic substrate between P-accumulating and denitrifying bacteria. The activated sludge consisted mainly of peculiar microorganisms recently described by Cech and Hartman (1990) and called “G bacteria”. The results obtained seem to be inconsistent with the general assumption that the G bacteria are characterized by anaerobic substrate uptake not connected with any polyphosphate metabolism. Supplementary anaerobic batch tests utilizing glucose, peptone and acetate as organic substrates show that the role of acetate in the biochemical mechanisms promoting EBPR may not be so essential as it has been assumed till now.
The genetic diversity of ayam ketawa (Gallus gallus domesticus, Linneaus, 1758) in Bangkalan District, Madura Island, Indonesia

Abstract. Abinawanto, Zulistiana T, Lestari R, Dwiranti A, Bowolaksono A. 2021. The genetic diversity of ayam ketawa (Gallus gallus domesticus, Linneaus, 1758) in Bangkalan District, Madura Island, Indonesia. Biodiversitas 22: 3145-3155. Ayam Ketawa, a variation of Gallus gallus domesticus Gallus gallus domesticus, comes from Sidendreng-Rappang (Sidrap) District, South Sulawesi, Indonesia. Apart from Sidrap, ayam ketawa farms are also found in Bangkalan District, on the island of Madura, Indonesia. Ayam ketawa from Bangkalan District often wins national level contests. Therefore, the research was carried out with the aim of knowing the genetic diversity of ayam ketawa in Kamal Subdistrict, Socah Subdistrict, and Burneh Subdistrict, based on bioacoustic, morphometric, and barcoding DNA analysis. The studied ayam ketawa consists of dangdut and slow types. The longest duration (6.00 ± 3.0) seconds was shown by ayam ketawa from Kamal Subdistrict, while the highest number of syllables (7.20 ± 5.80) came from Socah Subdistrict. The results of the Mann-Whitney test showed that eight morphological characters were significantly different (P <0.05) between ayam ketawa population in Kamal and Burneh subdistricts, namely body weight, femur length, shank length, shank circumference, wing length, comb height, third finger length, and breastbone length. Four morphological characters differed significantly (P <0.05) between ayam ketawa population in Kamal and Socah subdistricts, namely shank length, wing length, third finger length, and sternum length. Three morphological characters were significantly different (P <0.05) between the Burneh and Socah subdistricts population, namely body weight, femur length, and shank circumference. The analysis results of DNA Barcoding gene of the Cytochrome Oxidase subunit 1 (CO1) showed a genetic distance ranging from 0.025 to 1.872.
Direct Transformation of Edible Vegetable Waste into Bioplastics

Bioplastics with a wide range of mechanical properties were directly obtained from industrially processed edible vegetable and cereal wastes. As model systems, we present bioplastics synthesized from wastes of parsley and spinach stems, rice hulls, and cocoa pod husks by digesting in trifluoroacetic acid (TFA), casting, and evaporation. In this way, amorphous cellulose-based plastics are formed. Moreover, many other natural elements present in these plants are carried over into the bioplastics rendering them with many exceptional thermo-physical properties. Here, we show that, due to their broad compatibility with cellulose, amorphous cellulose can be naturally plasticized with these bioplastics by simply mixing during processing. Comparison of their mechanical properties with that of various petroleum based synthetic polymers indicates that these bioplastics have equivalent mechanical properties to the nondegrading ones. This opens up possibilities for replacing some of the nondegrading polymers with the.
A Review of Post-Study and Post-Task Subjective Questionnaires to Guide Assessment of System Usability

Usability is a key consideration when developing an interactive software application because of the various outcomes it can produce. Accordingly, numerous evaluation methods have been proposed, however, a recent review of usability methods concluded there is no current consensus on models applied to usability. While questionnaires are a commonly used measure, it is unclear which questionnaire(s) are most appropriate for a given context, so new usability researchers face confusion over which to select. To aid questionnaire selection, the appropriate type (post-study or post-task), general structure and content, specific advantages and disadvantages, aspects of usability covered, and psychometric quality should be considered. This paper presents a literature review and analysis of general post-study and post-task usability measures. Questionnaires are weighed up and discussed on each aspect, so practitioners can gain a holistic overview and identify relative strengths of individual questionnaires within their questionnaire type. Overall recommendations and specific questionnaire suggestions are provided for guidance, along with how future research can expand the review.
Contextual Learning Method, Learning Facility and Motivation in Relation to Sociology Learning Outcome

This study was aimed at examining the simultaneous effect of contextual learning methods, learning facilities, and motivation on the students’ learning outcome. A survey as a part of the quantitative research design was employed by utilizing 139 samples out of 210 population. To collect data, a questionnaire was distributed to the samples getting involved in the present study, and to ascertain that the instrument was valid and reliable, Pearson Product Moment and Cronbach Alpha were used to test this instrument. Data were stored in SPSS and analyzed using Multiple Regression Analysis after conducting some sets of testing including classical assumption test, normality test, collinearity, heteroskedasticity, and homoscedasticity test as a prerequisite on using multiple regression analysis. It was found that there was a significant correlation among the contextual learning method, learning facility, and motivation on the students’ learning achievement of sociology subject matter. The more often contextual learning was used, the more complete facility the school has, and the more motivated students have tended to have better learning achievement on sociology. Therefore, teachers, practitioners, and syllabus designers ought to pay close attention to the learning method, learning facility, and motivation to develop the students’ sociology achievement. Keywords—contextual learning methods, learning facilities, motivation, students’ learning outcome
of Birmingham Rigidity in routines and the development of resistance to change in individuals with Prader–Willi syndrome

Individuals with Prader-Willi syndrome (PWS) commonly show debilitating resistance to change, which has been linked to cognitive deficits in task switching. Anecdotal reports suggest that exposure to flexibility in routines during development may be beneficial for limiting subsequent resistance to change in people with PWS; which is consistent with a beneficial role of such exposure on the development of task switching, highlighted in typical children. Here we aim to investigate the development of resistance to change in individuals with PWS and hypothesise that exposure to increased rigidity in routines will be associated with increased subsequent resistance to change. Method An author compiled informant report interview and two previously validated questionnaires were administered to the caregivers of 10 individuals with PWS (5-23 years). The interview examined rigidity in routines and resistance to change across life stages defined by easily distinguishable events (before school; during primary school; during secondary school; after school; currently), using open ended and structured yes/no and five-point Likert questions. Open ended data were coded using an author compiled system. Responses from two additional informants; and data from the questionnaires were used to assess inter-informant reliability and concurrent validity of the structured questions. reliability of the open ended system; and reliability, internal consistency and behaviour
Molecular Conformation at the Crystal–Amorphous Interface in Polyethylene

Torsional-tapping AFM with supersharp carbon-whisker tips is used to explore the molecular conformations at the surface of a semicrystalline polymer. Images of the crystal–amorphous interface of oriented polyethylene have allowed us to measure hitherto inaccessible parameters that can be directly compared to polymer crystallization theories and molecular simulations, such as the length of stem-to-stem overhang. It has also been possible to identify both first- and second-neighbor folds and to determine the surface roughness of lamellae which we find approximately doubles the interfacial area. Finally, we calculate the interfacial density profile from the images and find it to be sigmoidal but narrower than values reported by SAXS measurements.
Transformer-Based Direct Hidden Markov Model for Machine Translation

The neural hidden Markov model has been proposed as an alternative to attention mechanism in machine translation with recurrent neural networks. However, since the introduction of the transformer models, its performance has been surpassed. This work proposes to introduce the concept of the hidden Markov model to the transformer architecture, which outperforms the transformer baseline. Interestingly, we find that the zero-order model already provides promising performance, giving it an edge compared to a model with first-order dependency, which performs similarly but is significantly slower in training and decoding.
Prevalence of Malaria Infections Among Patients in Gimbie Adventist Hospital Western Wollega, Oromia Regional State, Ethiopia

Malaria is a disease caused by protozoan parasites belonging to the genus Plasmodium. The five species of the parasite in human are P. falciparum, P. vivax, P. malariae, P.ovale and P. knowlesi. It is a major cause of morbidity and mortality worldwide, especially in young African children. Therefore, the objectives of this study were to assess the prevalence of malaria infection and associated factors among patients attending Gimbie Adventist Hospital in West Wollega, Oromia, Ethiopia. First, a retrospective study was carried out for the past ten years (2006-2016) to study the prevalence of malaria in the study area. Second, malaria suspected patients basedcross-sectional study was carried out from March to June, 2017. A random samplingtechnique was carried out to select representative study participants among the patient’s members. Structured questionnaires (n=130) and blood sample examinations were used for data collection. The data was entered and analyzed using SPSS 20 version. The prevalence of malaria in males was 71(65.7%) and in females were 37(34.3%). The greatest number of malaria case tested in the age group of 16-30 years old was 52(48.1%). Among 384 Malaria suspected patients who were recruited and ascertained for parasitaemia from the blood sample test, 108 patients were malaria positive. The overall prevalence of malaria infection was 28.1%, of which 58 (53.7%) were positive for P. falciparum and 34 (31.5%) for P. vivax and the remaining 16(14.8%) were mixed (P. falciparum + P. vivax). Major Plasmodium species identified in this study was P. falciparum (53.7%). Out of the screened patients 69.2% responded to sleep under the ITNs the previous night. The coverage of IRs was observed to be 12.3% during the study period. The higher prevalence of malaria could be the result of several factors as explained in this study. Therefore, effective malaria control measures should be implemented in order to reduce the prevalence of malaria infection among patients.
Monitoring Depression Trends on Twitter During the COVID-19 Pandemic: Observational Study

Background The COVID-19 pandemic has affected people’s daily lives and has caused economic loss worldwide. Anecdotal evidence suggests that the pandemic has increased depression levels among the population. However, systematic studies of depression detection and monitoring during the pandemic are lacking. Objective This study aims to develop a method to create a large-scale depression user data set in an automatic fashion so that the method is scalable and can be adapted to future events; verify the effectiveness of transformer-based deep learning language models in identifying depression users from their everyday language; examine psychological text features’ importance when used in depression classification; and, finally, use the model for monitoring the fluctuation of depression levels of different groups as the disease propagates. Methods To study this subject, we designed an effective regular expression-based search method and created the largest English Twitter depression data set containing 2575 distinct identified users with depression and their past tweets. To examine the effect of depression on people’s Twitter language, we trained three transformer-based depression classification models on the data set, evaluated their performance with progressively increased training sizes, and compared the model’s tweet chunk-level and user-level performances. Furthermore, inspired by psychological studies, we created a fusion classifier that combines deep learning model scores with psychological text features and users’ demographic information, and investigated these features’ relations to depression signals. Finally, we demonstrated our model’s capability of monitoring both group-level and population-level depression trends by presenting two of its applications during the COVID-19 pandemic. Results Our fusion model demonstrated an accuracy of 78.9% on a test set containing 446 people, half of which were identified as having depression. Conscientiousness, neuroticism, appearance of first person pronouns, talking about biological processes such as eat and sleep, talking about power, and exhibiting sadness were shown to be important features in depression classification. Further, when used for monitoring the depression trend, our model showed that depressive users, in general, responded to the pandemic later than the control group based on their tweets (n=500). It was also shown that three US states—New York, California, and Florida—shared a similar depression trend as the whole US population (n=9050). When compared to New York and California, people in Florida demonstrated a substantially lower level of depression. Conclusions This study proposes an efficient method that can be used to analyze the depression level of different groups of people on Twitter. We hope this study can raise awareness among researchers and the public of COVID-19’s impact on people’s mental health. The noninvasive monitoring system can also be readily adapted to other big events besides COVID-19 and can be useful during future outbreaks.
‘No Time for Quality’: Mechanisms of Local Governance in Russia

Abstract How does centralisation affect public goods provision in Russian municipalities? Drawing on the evidence from 68 interviews with municipal elites in four Russian regions, we demonstrate that, first, centralisation through excessive regulation encourages the provision of a higher quantity of public goods but does not encourage their quality. Short time horizons and haste lower the quality of goods even further. Moreover, centralisation favours municipalities with higher state capacity. Finally, risk-averse behaviour by officials leads to a lower quality of public goods.
Digitalising City Governance in Russia: The Case of the ‘Active Citizen’ Platform

Abstract This essay examines the role of civic tech in contemporary Russian governance through a data-driven analysis of the ‘Active Citizen’ platform deployed in Moscow. It shows that the way in which polls are conducted on the platform has various consequences, from serving the city administration’s PR needs to shuffling the power balance in various policy areas and effectively disempowering certain stakeholder groups, as well as helping the administration to increase control over a policy domain. At the same time, some platform uses actually empower citizens by engaging them in decision-making and offering grounds for further mobilisation.