Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward 6G Architecture for Energy-Efficient Communication in IoT-Enabled Smart Automation Systems

Energy-efficient communication has become the center of attention from various interdisciplinary fields, such as industrial automation, healthcare, and transportation, among others. Besides, proliferation in the artificial intelligence (AI)-based sixth-generation (6G) technology for achieving the smart automation system has caught the attention of both academia and industry. Most of the intelligent automation systems are formed by IoT-based user terminal (UT) devices for multimedia (i.e., video, audio, image, and text) content delivery with high clarity and efficiency. Customer satisfaction/perception, i.e., Quality of Experience (QoE), is an essential factor to be analyzed because the Quality of Service (QoS) is not a suitable candidate to portray the feelings and expectations of users during multimedia transmission. Therefore, the energy-efficient, entropy-aware communication, and QoE analysis through IoT devices are the dire need. This article focuses on how the energy-efficient communication and user’s QoE level can be captured through the UT device during multimedia transmission. Thus first, QoS-based joint energy and entropy optimization (QJEEO) algorithm is proposed. Second, the 6G-driven multimedia data structure model and framework are developed for modeling and evaluation of QoE with acquisition time. Third, the relationship between subjective test score (i.e., surveyed data) and objective performance metrics with mobility/speed of IoT-based devices for multimedia service is established. Fourth, the correlation model is proposed for integrating QoS parameters with estimated QoE perceptions. The experimental results indicate that QoE is modeled and evaluated with acquisition time and correlated with QoS parameter, i.e., packet loss ratio (PLR), and average transfer delay during energy-efficient multimedia transmission in 6G-based networks to improve the satisfaction level of customers.
A Preliminary Research to Develop Obstacle Detection System including Distance Measurement

Many nautical instruments such as radar, AIS and ECDIS support the seafarer’s Look-out on large vessels. However, there are few small ships equipped with these devices, while small ships account for 80% of the ships that suffered a marine accident. Therefore, in order to support the lookout of these ships, we developed a distance measurement system in addition to the obstacle detection system and evaluated its performance. With this system, we aim to develop a Look-out environment equivalent to the case where a small vessel is equipped with navigation equipment such as radar with only a camera and a personal computer, and to reduce the burden on the Look-out of the seafarers.
Finding Overlapping Clusters in a Highly Connected Graph from a Given Difference Density

In many fields, there may exist relationship among data or information used. Social network is a good example where relationship among members can be high and complex. Their interaction can be represented as a graph. Dividing such examples into smaller groups with similar characteristics can be translated into Graph Clustering. It is sub-field of clustering with numerous applications ranging from analysis of social network to computer network to bioinformatics. This work is an attempt to implement a novel overlapping clustering of a highly connected undirected unweighted graph. The main objective is to determine overlapped clusters in such a graph under a constrain of a specified different density. The approach starts with finding a spanning tree of the graph in order to discover all minimum cliques within the graph. These cliques are utilized by considering a clique with and an average sum of degrees of all three nodes. Such average cliques are the basis for expansion of clusters. Any clique or node that may already be a member of a cluster is allowed to be re-considered in the formation of other clusters. Hence, this enables overlapped clusters to appear. The process is carried out iteratively until all cliques and edges are considered. The two popular quality graph metrics, conductance and coverage, are selected to evaluate the overlapping clustering. Two examples of highly connected graphs are chosen for demonstration. The proposed approach is able to discover overlapping clusters from a given specific difference density. Result from this work can be used as a starting point analysis of highly connect graph, especially in the recent popularity of social network analysis.
Slice Sampling Reparameterization Gradients

Many probabilistic modeling problems in machine learning use gradient-based optimization in which the objective takes the form of an expectation. These problems can be challenging when the parameters to be optimized determine the probability distribution under which the expectation is being taken, as the naïve Monte Carlo procedure is not differentiable. Reparameterization gradients make it possible to efﬁciently perform optimization of these Monte Carlo objectives by transforming the expectation to be differentiable, but the approach is typically limited to distributions with simple forms and tractable normalization constants. Here we describe how to differentiate samples from slice sampling to compute slice sampling reparameterization gradients , enabling a richer class of Monte Carlo objective functions to be optimized. Slice sampling is a Markov chain Monte Carlo algorithm for simulating samples from probability distributions; it only requires a density function that can be evaluated point-wise up to a normalization constant, making it applicable to a variety of inference problems and unnormalized models. Our approach is based on the observation that when the slice endpoints are known, the sampling path is a deterministic and differentiable function of the pseudo-random variables, since the algorithm is rejection-free. We evaluate the method on synthetic examples and apply it to a variety of applications with reparameterization of unnormalized probability distributions.
Synthesis, Properties, and Theoretical Study of a Cation-Induced Iodoargentate Hybrid: [(PIP-H2)4·(Ag4I12)·H2O] n

A new cation-induced hybrid iodoargentate, [(PIP-H2)4·(Ag4I12)·H2O] n (1) (PIP = piperazine) has been obtained by the routine synthetic reaction in DMF solution and structurally determined. 1 crystallizes in monoclinic system, space group P21/n with unit cell parameters: a = 12.718(3), b = 9.3861(19), c = 20.098(4)Å, β = 90.33(3)°, V = 2399.1(8)Å3, Z = 4, C8H24Ag2I6N4O, M r = 1169.45, D c = 3.238 g/cm3, F(000) = 2080, μ(MoKα) = 9.356mm−1, the final R 1 = 0.0681 and wR = 0.1757 for 5255 observed reflections with I > 2σ(I). In 1, 0-D [Ag4I12]8− clusters were constructed from four vertex-sharing AgI4 tetrahedra and further linked by hydrogen bonds to give a 2-D layer. Luminescence can be detected in the title compound. Quantum chemistry calculation with DFT method was carried out to reveal its electronic structure.
Determiners are "conservative" because their meanings are not relations: evidence from verification

Quantificational determiners have meanings that are "conservative" in the following sense: in sentences, repeating a determiner's internal argument within its external argument is logically insignificant. Using a verification task to probe which sets (or properties) of entities are represented when participants evaluate sentences, we test the predictions of three potential explanations for the cross-linguistic yet substantive conservativity constraint. According to "lexical restriction" views, words like every express relations that are exhibited by pairs of sets, but only some of these relations can be expressed with determiners. An "interface filtering" view retains the relational conception of determiner meanings, while replacing appeal to lexical filters (on relations of the relevant type) with special rules for interpreting the combination of a quantificational expression (Det NP) with its syntactic context and a ban on meanings that lead to triviality. The contrasting idea of "ordered predication" is that determiners don't express genuine relations. Instead, the second argument provides the scope of a monadic quantifier, while the first argument selects the domain for that quantifier: the sequences with respect to which it is evaluated. On this view, a determiner's two arguments each have a different logical status, suggesting that they might have a different psychological status as well. We find evidence that this is the case: When evaluating sentences like every big circle is blue , participants mentally group the things specified by the determiner's first argument (e.g., the big circles) but not the things specified by the second argument (e.g., the blue things) or the intersection of both (e.g., the big blue circles). These results suggest that the phenomenon of conservativity is due to ordered predication.
Understanding the effects of language revitalization workshops using long-format speech environment recordings

Long-format speech environment (LFSE) recordings are increasingly used to understand language acquisition among young children (Casillas & Cristia 2019). But in language revitalization, older children are sometimes the largest demographic acquiring a language. In Teotitlan del Valle, Mexico, older children have participated in Zapotec language revitalization workshops since 2017. To better understand how these children use language, and to probe whether the language workshops impact language use, I invited learners to collect LFSE recordings. This study addresses two main questions: (1) what methodological challenges emerge when children ages 6-12 collect LFSE data? ; and (2) what do the data suggest about the effects of the Zapotec workshops? I argue that, while creating LFSE recordings with older children presents methodological challenges, the results are useful in highlighting the importance of not only teaching language skills, but of creating spaces where learners are comfortable using the Zapotec language.
Prediction of Web Service Anti-patterns Using Machine Learning Framework

Service-Oriented Architecture(SOA) can be implemented via web services which are a product framework that reinforces machine to machine communication over a system. Web services suﬀer from some setbacks due to bad programming practices design and implementation. These are called ”Anti-patterns”. Anti-Patterns are counter-productive and poor design practice choices that are conjectured to make software systems harder to maintain. Web service anti-patterns lead to evolution and maintenance problems in software systems. The prediction of anti-patterns in the early stages helps the developers and testers in ﬁxing the design issues. This stimulates the researchers to focus on the detection of web service anti-patterns, to help the unskilled software developers and designers to improve the quality of services being provided.
Design Form and Function Prediction From a Single Image

Estimating the form and functional performance of a design in the early stages can be crucial for a designer for effective ideation Humans have an innate ability to guess the size, shape, and type of a design from a single view. The brain fills in the unknowns in a fraction of a second. However, humans may struggle with estimating the performance of designs in the early stages of the design process without making prototypes or doing back-of-the-envelope calculations. In contrast, machines need information about the full 3D model of a design to understand its structure. Machines can estimate the performance using pre-defined rules, expensive numerical simulations, or machine learning models. In this paper, we show how information about the form and functional performance of a design can be estimated from a single image using machine learning methods. Specifically, we leverage the image-to-image translation method to predict multiple projections of an image-based design. We then train deep neural network models on the predicted projections to provide estimates of design performance. We demonstrate the effectiveness of our method by predicting the aerodynamic performance from images of aircraft models. To estimate ground truth aero-dynamic performance, we run CFD simulations for 4045 3D aircraft models from the ShapeNet dataset and use their lift-to-drag ratio as the performance metric. Our results show that single images do carry information for both form and functional performance. From a single image, we are able to produce six additional images of a design in different orientations, with an average Structural Similarity Index score of 0.872. We also find image-translation methods provide a promising direction in estimating the performance of design. Using multiple images of a design (gathered through image-translation) to predict design performance yields a recall value of 47%, which is 14% higher than a base guess, and 3% higher than using a single image. Our work identifies the potential and provides a framework for using a single image to predict the form and functional performance of a design during the early-stage design process. Our code and additional information about our work are available at http://decode.mit. edu/projects/formfunction/.
Individually Vulnerable, Collectively Safe

Older adults are especially vulnerable to online cybersecurity and privacy (SP) threats, such as phishing, ransomware, and targeted misinformation campaigns. Prior work has suggested that this vulnerability may be addressed with the design of social SP interfaces, such that groups of individuals might work together on behalf of one another to manage SP threats collectively. To this end, we present findings from a qualitative inquiry conducted with older adults and members of technology-rich middle-income households in urban India, where technology users have been shown to engage in relatively more social SP practices. Our research examines the collaborative behaviors enacted by different members of the household for protection from SP threats. In particular, we show how self-appointed family technology managers straddle the line between stewardship and paternalism in their efforts to protect older adults from perceived digital threats. We also offer design implications for supporting collaborative cybersecurity within households based on the insights derived from our analysis.
A 3D Model for Visualizing the LOD Cloud

The LOD (Linked Open Data) cloud has been constantly increasing and it already contains thousands of published datasets. Existing visualizations, like the classical Linking Open Data cloud diagram, are useful for getting an overview of its size, the contained datasets and their connectivity. However, it hardly supports the processes of dataset monitoring, navigation and dataset discovery. For this reason, in this thesis we propose and evaluate a novel interactive 3D visualization that adopts the metaphor of urban area: each dataset is visualized as a building, whose features (e.g. volume) re ect various dataset's features (e.g. number of triples), while roads/bridges and the proximity of the buildings indicate the commonalities of the datasets. The introduced approach supports diverse types of buildings and various placement algorithms. The visualization is interactive i.e. it allows the user to zoom in any part of the model, to change the perspective, to change the shape of the buildings and their placement, to see all the connections or only those of one dataset, along with others. We explain in details the construction process of this model, we apply it over real datasets (including the entire LOD cloud) and we describe its usefulness for the coverage of user needs. Finally, the thesis reports the results of a task-based evaluation with users, which conducted and showed that the majority of the participants (a) prefer this model (to the classical 2D diagram), (b) they rate it as more useful, and (c) using this model, they achieved higher success rates in tasks that were assigned to them. ́Ενα 3D Μοντέλο για την Οπτικοποίηση του Νέφους Ανοικτών Διασυνδεδεμένων Δεδομένων
Structured Projection-free Online Convex Optimization with Multi-point Bandit Feedback

We consider structured online convex optimization (OCO) with bandit feedback, where either the loss function is smooth or the constraint set is strongly convex. Projection-free methods are among the most popular and computationally efficient algorithms for solving this problem, mainly due to their ability to handle convex constraints appearing in machine learning for which computing projections is often impractical in high-dimensional settings. Despite the improved regret bound results for the full-information setting where the gradients of the functions are readily available, it remains unclear whether simple projection-free zero-order algorithms become more efficient for structured OCO problems in the case when multiple function values can be sampled at each time instance. In this paper, we develop some simple projection-free algorithms and prove that they indeed achieve the same improved regret bounds as the full-information case under various additional problem structures. This implies that leveraging the structural properties of the problem compensates for the lack of access to the gradients. Experiments on the online matrix completion reveal several attractive advantages of the proposed algorithms, including their simplicity, easy implementation, and effectiveness, as they outperform other competing algorithms.
Transitional care to caregivers

e20200394 http://dx.doi. org/10.1590/0034-7167-2020-0394 8 of ABSTRACT Objective: To identify the needs of caregivers of dependent older people related to self-care in the transition from hospital to home. Methods: Integrative literature review that followed a predefined protocol, carried out from March to May 2019 in the platforms EBSCO, B-On, Scopus, Web of Science, and Joanna Briggs Institute. Descriptors and eligibility criteria were defined for the bibliographic sample, which was ten articles. The search was limited to articles published between 2015 and 2019 to guarantee evidence topicality. Results: The needs of caregivers related to transitional care can be grouped into five categories: needs in the transition into the role of caregiver; needs related to self-care of caregivers themselves; health needs; economic needs; and social and collective needs. Final considerations: The work developed by nurses regarding transitional care of caregivers must have two focuses: managing care provided to dependent older people and managing the needs of caregivers and the care offered to them. Descriptors: Transitional Care; Hospitalization; Caregivers; Elderly; Patient Discharge.
Optogenetic Cardiac Pacing

Optogenetics combines the biological techniques of optics and genetics and uses light to control the activities of living tissues such as neurons and heart. Optogenetic actuators including channelrhodopsin (ChR), halorhodopsin (NpHR), and archaerhodopsin specifically provide for neuronal or cardiac controls. The clinical translation of cardiac optogenetics will include human and larger mammalian animal model applications and ultimately optogenetics may have the power to restore normal heart rhythm.
A Flexible Model for Benchmarking the Energy Usage of Automotive Lithium-Ion Battery Cell Manufacturing

The increasing use of electric vehicle batteries in the world has a significant impact on both society and the environment. Thus, there is a need for the availability of transparent information on resource allocation. Battery manufacturing process details in this regard are not available in academia or the public. The available energy data on manufacturing has a high variation. Furthermore, different process steps have different energy and material demands. A process model can benchmark the energy usage, provide detailed process data, and compare various cell productions which in turn can be used in life-cycle assessment studies to reduce the variation and provide directions for improvements. Therefore, a cell manufacturing model is developed for the calculation of energy and material demands for different battery types, plant capacities, and process steps. The model consists of the main process steps, machines, intermediate products and building service units. Furthermore, the results are validated using literature values. For a case study of a 2 GWh plant that produces prismatic NMC333 cells, the total energy requirement on a theoretical and optimal basis is suggested to be 44.6Whinproduction/Whcellcapacity. This energy consumption in producing batteries is dominated by electrode drying, and dry room. Energy usage for a variety of cell types for a similar plant capacity shows that the standard deviation in the results is low (47.23±13.03Wh/Wh).
Interaction of cobalt nanoparticles with plants: a cytogenetical aspect

In vivo cytogenetical assay in root meristems has been carried out to study the effect of cobalt and cobalt oxide nanos on active mitotic index and chromosomal aberrations of green manure crop, Sesbania pea. Nanoparticles are nanosize particles and can enter freely into the cells and can interfere in cell's normal function. Studies to justify its probable after-effects on living beings are scarce. So it is important to study its effect on living beings. For this purpose, seeds of Sesbania cannabina variety ND-1 were soaked in distilled water for 14 hours and after soaking, the seeds were treated with three different treatments, namely, nano-cobalt, nano-cobalt oxide and ethanol for three hours. The treated root meristems exhibited various types of chromosomal aberrations such as metaphasic plate distortion, unorientation at metaphase, breaking of chromosomes, fragmentation, spindle dysfunctioning, stickiness, scattering, precocious movement at metaphase and bridge, unequal separation, multiple bridge, fragmentation, scattering, laggard and unorientation at anaphase, etc.
Cervical Epidural Anesthesia as a Sole Technique in Breast Cancer with Multiple Comorbidities

Malti Devi, 62 years female, case of breast cancer was posted for right sided Modified radical mastectomy (MRM). She was diabetic with chronic kidney disease (CKD) stage 3. CEA (Cervical epidural anaesthesia) was planned at C7-T1 midline space. Loss was resistance was achieved at 4.5 cm and the catheter was fixed at 12 cm. 10 ml of 0.375% ropivacaine was given through the catheter. After 10 minutes, further 5 ml of 0.375% of ropivacaine was given. For sedation, 50 mcg of fentanyl and 1 mg midazolam were administered. Sensory block was achieved from C7-T6. Surgery was conducted smoothly under CEA with good analgesia. She was administered 1 mg of epidural morphine for postoperative analgesia. Her average NRS was 3/10. Her satisfaction score was 80%. CEA provides stable cardiorespiratory status and thus, it can be used as a sole anaesthetic technique in patients with CKD and ASA 3 or 4 Patients.