Miracle-dz/UniFAR-FTUs huggingface dataset:
Robot-aided assessment of lower extremity functions

The assessment of sensorimotor functions is extremely important to understand the health status of a patient and its change over time. Assessments are necessary to plan and adjust the therapy in order to maximize the chances of individual recovery. Nowadays, however, assessments are seldom used in clinical practice due to administrative constraints or to inadequate validity, reliability and responsiveness. In clinical trials, more sensitive and reliable measurement scales could unmask changes in physiological variables that would not be visible with existing clinical scores. In the last decades robotic devices have become available for neurorehabilitation training in clinical centers. Besides training, robotic devices can overcome some of the limitations in traditional clinical assessments by providing more objective, sensitive, reliable and time-efficient measurements. However, it is necessary to understand the clinical needs to be able to develop novel robot-aided assessment methods that can be integrated in clinical practice. This paper aims at providing researchers and developers in the field of robotic neurorehabilitation with a comprehensive review of assessment methods for the lower extremities. Among the ICF domains, we included those related to lower extremities sensorimotor functions and walking; for each chapter we present and discuss existing assessments used in routine clinical practice and contrast those to state-of-the-art instrumented and robot-aided technologies. Based on the shortcomings of current assessments, on the identified clinical needs and on the opportunities offered by robotic devices, we propose future directions for research in rehabilitation robotics. The review and recommendations provided in this paper aim to guide the design of the next generation of robot-aided functional assessments, their validation and their translation to clinical practice.
Sustainable product development by means of personalization – paradox or solution?

Personalization of products and services entails not only risks but also potentials for sustainability. During the product development process, it is crucial to take into account future usage patterns and their variability. Even if the product itself is not personalized, a user-centered approach during the entire life cycle can unlock many potentials. Avoiding unnecessary functions and tailoring a product precisely to its user’s needs can lead to optimized sustainability performance during its use. Moreover, by developing and offering personalizable products that meet the requirements of the respective user, companies can tap into new market opportunities and increase their competitiveness. As a methodological basis, we introduce a combination of the Stuttgart models of personalization and personalized product development with life cycle thinking aspects and circularity strategies. In an interactive workshop the integrated model is discussed and participants can locate their own work and perspective within the broader personalization scheme. Different opportunities of personalization are highlighted from an environmental point of view.
IoT Hub as a Service (HaaS): Data-Oriented Environment for Interactive Smart Spaces

Smart devices around us produce a considerable volume of data and interact in a wide range of scenarios that guide the evolution of the Internet of Things (IoT). IoT adds informative and interactive aspects to our living spaces, converting them into smart spaces. However, the development of applications is challenged by the fragmented nature due to the vast number of different IoT things, the format of reported information, communication standards, and the techniques used to design applications. This paper introduces IoT Hub as a Service (HaaS), a data-oriented framework to enable communication interoperability between the ecosystem’s entities. The framework abstracts things' information, reported data items, and developers' applications into programmable objects referred to as Cards. Cards represent specific entities and interactions of focus with meta-data. The framework then indexes cards’ meta-data to enable interoperability, data management, and application development. The framework allows users to create virtual smart spaces (VSS) to define cards' accessibility and visibility. Within VSS, users can identify accessible data items, things to communicate, and authorized applications. The framework, in this paper, defines four types of Cards to represent: participating IoT things, data items, VSS, and applications. The proposed framework enables the development of synchronous and asynchronous applications. The framework dynamically creates, updates, and links the cards throughout the life-cycle of the different entities. We present the details of the proposed framework and show how our framework is advantageous and applicable.
OUHCIR at the NTCIR-16 Data Search 2 Task

In this paper, we report our work and discuss the results for NTCIR-16 DataSearch-2 IR subtask. NTCIR-16 Data Search-2 was organized to improve the present knowledge and promote the concepts of dataset search among IR researchers. In this particular subtask, we tried to perform ad-hoc retrieval for datasets based on given queries. While this task was available in English and Japanese, we decided to only compete for the English subtask. We sought to perform the ranking of datasets by using traditional BM25-based ranking functions and recent language models. During the evaluation experiments, we also explored the impact of metadata features on the performance of dataset ranking. Our best performing submission achieved a score of 0.153, 0.161 and 0.174 in nDCG@10, nERR@10, and Q-measure, respectively. In all the metrics, this run was ranked 13th among 25 submitted runs.
fuys at the NTCIR-16 QA Lab-PoliInfo-3 Budget Argument Mining Subtask

This paper reports on the achievements of Budget Argument Mining subtask of the NTCIR-16 QA Lab-PoliInfo-3 task of fuys team. We have assigned ArgumentClass and RelatedID in different ways. ArgumentClass was assigned using BERT. We also thought that the accuracy could be improved by adding the flag indicating whether a speaker is a legislator or not (“giin-flag”). RelatedID was assigned using keyword extraction with TFIDF. The results showed good results for ArgumentClass, but the improvement in accuracy of RelatedID could not be confirmed. Although there was a difference in the results for the “giin-flag”, the difference was small, and no advantage was found with or without the “giin-flag”.
A comparative study between support vector machine and support vector data description in bank telemarketing

Machine learning (ML) is playing more and more important role in the banking system. A supervised ML technique, support vector machine, and an unsupervised ML technique, support vector data description, are applied in the bank telemarketing area to predict that who possibly will buy the term deposit. The results show that SVM outperforms the SVDD based on the overall accuracy and AUC values. The overall accuracy for SVM model attains to 97.30% while the accuracy for SVDD model is a bit higher than random guessing. The AUC values are 0.9867 and 0.8565 for SVM and SVDD model, respectively. SVM model is more su itable for binary classification problem compared to SVDD.
STUDY OF CO 2 /H 2 O ICE ABUNDANCE RATIOS IN NEARBY GALAXIES WITH THE AKARI NEAR-INFRARED SPECTROSCOPY

We study CO 2 = H 2 O ice abundance ratios in nearby galaxies using AKARI near-infrared slit spectroscopy. Past studies of the ices intensively examined CO 2 = H 2 O ratios mainly in our Galaxy, and found that there were considerable variations in the CO 2 = H 2 O ratios from object to object. The cause of the variations is, however, still under debate. As a result of the analysis of our sample that includes 1031 regions in 158 galaxies, the CO 2 = H 2 O ratios are in a range of 0.05{0.30. In the dataset, we (cid:12)nd that the CO 2 = H 2 O ratios positively correlate with the Br (cid:11) /PAH 3.3 (cid:22) m ratios which re(cid:13)ect the massive star formation activity. Furthermore, we (cid:12)nd that the CO 2 = H 2 O ratios positively correlate with the speci(cid:12)c star formation rates of the galaxies where the ices are detected, that re(cid:13)ect the evolutionary stage of a galaxy. These results suggest that the CO 2 = H 2 O ratios are enhanced in active star-forming regions and young galaxies.
Six Dimensions Describe Action Understanding: The ACT-FASTaxonomy

Humans engage in a wide variety of different actions and activities. These range from simple motor actions like reaching for an object, to complex activities like governing a nation. Navigating everyday life requires people to make sense of this diversity of actions. We suggest that the mind simpli ﬁ es this complex domain by attending primarily to the most essential features of actions. Using a parsimonious set of action dimensions, the mind can organize action knowledge in a low-dimensional representational space. In seven studies, we derive and validate such an action taxonomy. Study 1 uses large-scale text analyses to generate and test potential action dimensions. Study 2 validates interpretable labels for these dimensions. Studies 3 – 5 demonstrate that these dimensions can explain human judgments about actions. We perform model selection on data from these studies to arrive at the optimal set of six psychological dimensions, together forming the Abstraction, Creation, Tradition, Food, Animacy, Spiritualism Taxonomy (ACT-FAST). Study 6 demonstrates that ACT-FAST can predict socially relevant qualities of actions, including how, when, where, why, and by whom they are performed. Finally, Study 7 shows that ACT-FAST can explain action-related patterns of brain activity using naturalistic functional MRI (MRI). Together, these studies reveal the dimensional structure the mind applies to organize action concepts.
Failure detection for quasi LPV systems

By using the concept of parameter varying (CA)invariant subspace and parameter varying unobservability subspace, this paper investigates the problem of fault detection and isolation for quasi linear parameter varying (qLPV) systems. The so called detection filters approach, formulated as the fundamental problem of residual generation (FPRG) for linear time invariant (LTI) systems is extended for a class of qLPV systems. The parameter dependence in the state matrix of these qLPV systems is assumed to be in affine form. The question of stability is addressed in the terms of Lyapunov quadratic stability by using an LMI technique. A numerical example is also provided.
Pollinator Habitat on the University of Richmond Campus: Assessing the Success of Pollinator Meadows in the Gambles Mill Eco-Corridor

: Globally, many insect pollinator populations are declining in response to anthropogenic harms including habitat loss due to land-use change and urbanization, climate change, increasing pesticide use, invasive species introductions, and increased pathogen transmission. In order to protect these insects, and the benefits they provide through pollination, habitat must be protected. Much of the effort to protect insect pollinator habitat is occurring in urban areas, where pollinators may struggle to find the resources they need to survive. The purpose of this study was to assess the success of three pollinator meadows created within the Gambles Mill Eco-Corridor (Eco-Corridor) on the University of Richmond (UR) campus in Richmond, VA. These meadows were designed to provide habitat to insect pollinators as part of UR’s recertification process as a Bee City USA certified Bee Campus. In order to assess the quality of habitat provided by these meadows, they were compared to three other sites on campus containing managed flower beds. At each site, five 1x1 meter quadrats were laid and the percent ground cover, individual number of plants, number of plant species, and presence of pollinators within each quadrat were recorded. Each presumed plant species was photographed and later identified, and its nativity to the area was noted. Results of these surveys suggest that the pollinator meadows do provide better habitat for insect pollinators than managed flower beds on campus. This information may be used to suggest to the campus Landscape Services Department ways to improve managed flower beds in terms of pollinator habitat. However, this study also revealed flaws within the pollinator meadows, and indicates a need for further planting projects to improve habitat on campus. ground cover values observed in each quadrat at a single site were averaged to get a value for that site. Each site was then rated based on its percent ground cover using the Braun-Blanquet scale. The number of individual plants observed in each quadrat were also averaged at each site. Two two-tailed t-tests assuming unequal variances were then performed to determine if any difference in ground cover or number of individual plants between site types was significant. The plant species observed across all of the quadrats of each site type were aggregated to provide total numbers of species observed within both site types for comparison. The percent of species observed which were native to the area was then calculated for each site type for comparison. The presence and species identifications of any pollinators observed in each site type were also compared.
A comparison of precipitation and ﬁ ltration-based SARS-CoV-2 recovery methods and the in ﬂ uence of temperature, turbidity, and surfactant load in urban wastewater of the Total Environment

has become a complimentary surveillance tool during the SARS-CoV-2 pan- demic. Viral concentration methods from wastewater are still being optimised and compared, whilst viral recovery under different wastewater characteristics and storage temperatures remains poorly understood. Using urban waste- water samples, we tested three viral concentration methods; polyethylene glycol precipitation (PEG), ammonium sul-phateprecipitation(AS), andCP select ™ InnovaPrep® (IP) ultra ﬁ ltration. WefoundnomajordifferenceinSARS-CoV- 2 and faecal indicator virus (crAssphage) recovery from wastewater samples ( n = 46) using these methods, PEG slightly (albeit non-signi ﬁ cantly), outperformed AS and IP for SARS-CoV-2 detection, as a higher genome copies per litre (gc/l) was recorded for a larger proportion of samples. Next generation sequencing of 8 paired samples revealed non-signi ﬁ cant differencesin thequalityofdatabetweenASandIP, thoughIPdataqualitywasslightlybetterandless variable. A controlledexperiment assessed the impact ofwastewatersuspended solids (turbidity; 0 – 400 NTU), surfac-tantload(0 – 200mg/l),andstoragetemperature(5 – 20°C)onviralrecoveryusingtheASandIPmethods.SARS-CoV-2 recoverieswere > 20%withASand < 10%withIPinturbidsamples,whilstviralrecoveriesforsampleswithadditional surfactant were between 0 – 18% for AS and 0 – 5% for IP. Turbidity and sample storage temperature combined had no signi ﬁ canteffectonSARS-CoV-2recovery( p > 0.05),whilstsurfactantandstoragetemperaturecombinedweresignif-icant negativecorrelates( p < 0.001and p < 0.05, respectively). Inconclusion, our results showthat choiceofmethod- ology had small effect on viral recovery of SARS-CoV-2 and crAssphage in wastewater samples within this study. In contrast, sample turbidity, storage temperature, and surfactant load did affect viral recovery, highlighting the need for careful consideration of the viral concentration methodology used when working with wastewater samples.
Keeping Privacy Labels Honest

At the end of 2020, Apple introduced privacy nutritional labels, requiring app developers to state what data is collected by their apps and for what purpose. In this paper, we take an in-depth look at the privacy labels and how they relate to actual transmitted data. First, we give an exploratory statistically evaluation of 11074 distinct apps across 22 categories and their corresponding privacy label or lack thereof. Our dataset shows that only some apps provide privacy labels, and a small number self-declare that they do not collect any data. Additionally, our statistical methods showcase the differences of the privacy labels across application categories. We then select a subset of 1687 apps across 22 categories from the German App Store to conduct a no-touch traffic collection study. We analyse the traffic against a set of 18 honey-data points and a list of known advertisement and tracking domains. At least 276 of these apps violate their privacy label by transmitting data without declaration, showing that the privacy labels’ correctness was not validated during the app approval process. In addition, we evaluate the apps’ adherence to the GDPR in respect of providing a privacy consent form, through collected screenshots, and identify numerous potential violations of the directive.
Alcoholic Liver Injury in the Rat Is Associated with Reduced Expression of Peroxisome Proliferator- (cid:1) (PPAR (cid:1) )-Regulated Genes and Is Ameliorated by PPAR (cid:1) Activation

Alcoholic liver disease is associated with a state of hepatic fatty acid overload. We examined the effect of ethanol and different types of dietary fat on the expression of mRNA for liver fatty acid binding protein ( L -FABP), peroxisome proliferator-acti-vated receptor- (cid:1) (PPAR (cid:1) ), and peroxisomal fatty acyl CoA oxidase (FACO). Four groups of rats ( n (cid:1) 5) were fed intragas-trically, a liquid diet with or without ethanol (10–16 g/kg/day) for 4 weeks. Pair-fed controls received isocaloric amounts of dextrose. The source of fat was either corn oil or fish oil. Ethanol- fed rats developed fatty liver, necrosis, and inflammation; the changes were more severe in the fish oil-ethanol (FE) rats. PPAR (cid:1) mRNA levels were not different between groups, although there was a trend toward increased levels in ethanol-fed rats. We calculated L -FABP/PPAR (cid:1) and FACO/PPAR (cid:1) ratios as a measure of FACO and L -FABP up-regulation relative to PPAR (cid:1) expression. Both FACO/PPAR (cid:1) and L -FABP/PPAR (cid:1)
PROJECT-BASED LEARNING MODEL TO PROMOTE STUDENTS CRITICAL AND CREATIVE THINKING SKILLS

Abstra ct: This study aimed to assess the worthiness of the project-based learning model in training critical and creative thinking skills on colloidal material. This research is a pre-experimental design with a one group pretest-posttest design. 31 students of XI MIPA 4 at MAN 1 Mojokerto were the targets studied in this study. The results of this study are: 1) The average percentage of the project-based learning treatment obtained is 78% in the good category (1st meeting) and 88% in the very good category (2nd meeting). 2) The activity of students is declared good with a percentage of 88%. 3) Critical and creative thinking skills have high criteria, as shown in the results of N-Gain 0.70, 0.73, and 0.73. 4) Student learning outcomes increase, which indicated from one complete student to 28 complete students. 5) A total of 95% positive responses were obtained from 31 students on the Project-Based Learning model. So the conclusion that can be drawn is that the project based learning model can train students' critical and creative thinking skills on colloidal material. project based learning model can be used as an alternative learning strategy to practice critical and creative thinking skills as the demands of 21st-century skills. It is more maximal and meaningful so that the desired learning activities and better results study can be achieved.
Mortality of

Objectives The purpose of this study was to evaluate the health consequences of employment in the lead-smelting industry. Methods A mortality study of 1388 workers and laborers in production and maintenance departments was conducted in an Italian lead-smelting plant. The vital status of cohort members was determined from 1950 to 1992. Standardized mortality ratios were calculated for specific causes of death on the basis of national and regional reference rates. The relative risk for selected causes of death was also modeled as a function of age, calendar period, latency, and duration of elnployment with Poisson regression analysis. Resi~lts A significant 4.5-fold excess mortality from pneumoconiosis and other diseases of the respiratory system was observed, but the risk of pneulnoconiosis did not show a significant trend by duration of employment. Mortality from all cancers, stomach cancer, and lung cancer was lower than expected. The standardized mortality ratios for genitourinary diseases and kidney cancer were not significantly elevated, but the Poisson regression analysis showed that both risks increased significantly by duration of employment. C O ~ C ~ U S ~ O ~ S These findings provide limited evidence that long-term employment in lead-smelting plants increases the risk of genitourinary diseases and kidney cancer. The observed increase in mortality from pneumoconiosis and other diseases of the respiratory system was more likely related to silica exposure in other workplaces. No excess risk of stomach cancer and lung cancer was observed in this cohort. The present study designed to evaluate cause-specific mortality among of a
Decentralized yet Unifying: Digital Media and Solidarity in Hong Kong's Anti-Extradition Movement

Can decentralized, digitally-enabled movements sustain solidarity over time? What is the role of digital media in such a process? While existing studies point to the possibility of maintaining solidarity via digital media, the patterns that underlie such a process remain understudied. We focus on the case of the 2019 Anti-Extradition Law Amendment Bill Movement in Hong Kong and one of the primary digital platforms for mobilization, the LIHKG forum. We highlight the importance of the intersection of rhetoric and emotions and contend that LIHKG users develop practices to foster solidaristic contents while inhibiting divisive ones. Empirically, we analyze millions of discussion posts on LIHKG with rich text and emoji data. We document the rising trend of online solidaristic contents in both rhetoric and emotions despite the contemporaneous tactical radicalization and demonstrate their co-occurrence. This study has implications on the role of digital media and the sustainability of decentralized collective action.
Detection and Evaluation of Driver Distraction Using Machine Learning and Fuzzy Logic

In addition to vehicle control, drivers often perform secondary tasks that impede driving. Reduction of driver distraction is an important challenge for the safety of intelligent transportation systems. In this paper, a methodology for the detection and evaluation of driver distraction while performing secondary tasks is described and an appropriate hardware and a software environment is offered and studied. The system includes a model of normal driving, a subsystem for measuring the errors from the secondary tasks, and a module for total distraction evaluation. A new machine learning algorithm defines driver performance in lane keeping and speed maintenance on a specific road segment. To recognize the errors, a method is proposed, which compares normal driving parameters with ones obtained while conducting a secondary task. To evaluate distraction, an effective fuzzy logic algorithm is used. To verify the proposed approach, a case study with driver-in-the-loop experiments was carried out, in which participants performed the secondary task, namely chatting on a cell phone. The results presented in this research confirm its capability to detect and to precisely measure a level of abnormal driver performance.