Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effectiveness of a Neurofeedback-Assisted Mindfulness Training Program Using a Mobile App on Stress Reduction in Employees: Randomized Controlled Trial

Background Mindfulness-based training programs have consistently shown efficacy in stress reduction. However, questions regarding the optimal duration and most effective delivery methods remain. Objective This research explores a 4-week neurofeedback-assisted mindfulness training for employees via a mobile app. The study’s core query is whether incorporating neurofeedback can amplify the benefits on stress reduction and related metrics compared with conventional mindfulness training. Methods A total of 92 full-time employees were randomized into 3 groups: group 1 received mobile mindfulness training with neurofeedback assistance (n=29, mean age 39.72 years); group 2 received mobile mindfulness training without neurofeedback (n=32, mean age 37.66 years); and group 3 were given self-learning paper materials on stress management during their first visit (n=31, mean age 38.65 years). The primary outcomes were perceived stress and resilience scales. The secondary outcomes were mindfulness awareness, emotional labor, occupational stress, insomnia, and depression. Heart rate variability and electroencephalography were measured for physiological outcomes. These measurements were collected at 3 different times, namely, at baseline, immediately after training, and at a 4-week follow-up. The generalized estimating equation model was used for data analysis. Results The 4-week program showed significant stress reduction (Wald χ22=107.167, P<.001) and improvements in psychological indices including resilience, emotional labor, insomnia, and depression. A significant interaction was observed in resilience (time × group, Wald χ42=10.846, P=.02). The post hoc analysis showed a statistically significant difference between groups 1 (least squares mean [LSM] 21.62, SE 0.55) and 3 (LSM 19.90, SE 0.61) at the posttraining assessment (P=.008). Group 1 showed a significant improvement (P<.001) at the posttraining assessment, with continued improvements through the 1-month follow-up assessment period (LSM 21.55, SE 0.61). Physiological indices were analyzed only for data of 67 participants (22 in group 1, 22 in group 2, and 23 in group 3) due to the data quality. The relaxation index (ratio of alpha to high beta power) from the right electroencephalography channel showed a significant interaction (time × group, Wald χ22=6.947, P=.03), with group 1 revealing the highest improvement (LSM 0.43, SE 0.15) compared with groups 2 (LSM –0.11, SE 0.10) and 3 (LSM 0.12, SE 0.10) at the 1-month follow-up assessment. Conclusions The study demonstrated that the neurofeedback-assisted group achieved superior outcomes in resilience and relaxation during the 4-week mobile mindfulness program. Further research with larger samples and long-term follow-up is warranted. Trial Registration ClinicalTrials.gov NCT03787407; https://clinicaltrials.gov/ct2/show/NCT03787407
Insights from an ICT4D Initiative in Kenya's Immunization Program: Designing for the Emergence of Sociomaterial Practices

ICT4D initiatives hold the potential to transform health service delivery in settings of poverty, yet, in practice, they face many of the same implementation complexities and coordination challenges as the global health and development programs that they aim to streamline or strengthen. Researchers and practitioners alike are now quick to observe that “context matters”, but such an observation does not amount to a coherent alternative vision of more appropriate ICT4D design and implementation. In this paper, we draw on the metaphor of imbrication to elucidate the iterative process by which ICTs become entangled with particular contexts of use. Our longitudinal ethnographic study examines the implementation and iterative redesign of an Internet of things (IoT) technology that collects real-time data and alerts health workers of disruptions in the cold storage of vaccines in Kenya. Extending recent work on imbrication, we show that technologies imbricate not only with the social context but also with local material infrastructure and that designers play a limited yet clearly consequential role in this process. To explain these findings, we highlight instances of material “back talk” and concomitant practice breakdown in which initial attempts to shape a situation yield puzzling or unappreciated consequences, which lead designers to accommodate material realities and, ultimately, pursue unanticipated courses of action. Drawing on these conceptual tools, we reveal six overlapping activities through which designers may guide the emergence of sociomaterial practices. We say that they design for the emergence of sociomaterial practices to underscore that designers cannot predict or control all contextual complexities, though they can adapt to them when they arise. Based on our insights about this process, we develop three contributions. First, we offer fresh perspective on the longstanding concern with local context in ICT4D research. Second, we suggest that our notion of designing for the emergence of sociomaterial practices is relevant for and adds to contextually aware design research frameworks such as action design research. Finally, we propose that ICT4D practitioners should attend to practice breakdowns and material back talk as they grapple with the complexities of the implementation bottleneck in global health and development.
Tolerance for Validation in Omnichannel Retail Stores: Enabling Logistics and Supply Chain

Mobile technologies are increasingly used as a data source to enable big data analytics that enable inventory control and logistics planning for omnichannel businesses. This paper focuses on the use of mobile technologies to facilitate customers’ shopping in physical retail stores and associated implementation challenges. First, we introduce three emerging mobile shopping checkout processes in the retail store. Second, we suggest that new validation procedures (i.e., exit inspections) necessary for implementation of mobile technology-enabled checkout processes may disrupt traditional retail service processes. We propose a construct labeled “tolerance for validation” defined as customer reactions to checkout procedures. We define and discuss five dimensions: Tolerance for (1) unfair process; (2) changes in validation process; (3) inconvenience; (4) mistrust; and (5) privacy intrusion. We develop a measurement scale for the proposed construct and conduct a study among 239 customers. Our results show that customers have higher tolerance for validation under scenarios in which mobile technologies are used in the checkout processes, as compared to the traditional self-service scenario in which no mobile technology is used. In particular, the customers do not show a clear preference for specific mobile shopping scenarios. These findings contribute to our understanding of a challenge that omnichannel businesses may face as they leverage data from digital technologies to enhance collaborative planning, forecasting, and replenishment processes. The proposed construct and measurement scales can be used in future work on omnichannel retailing.
Consumers' values and attitudes and their relation to the consumption of pork products: a study from Q-PorkChains in Brazil

Consumers' attitudes and personal values were assessed, investigating if those constructs affect the consumption of pork products. Empirical data was collected through a survey performed with 482 consumers in Brazil, according to Q-PorkChains project definitions. Attitudes towards the environment and nature are quite positive, although ethnocentrism is also present. Industrial food production seems to be an accepted system, but consumers are showing that environmental sustainability must not be forgotten. Consumers with more ‘traditionalist’ values prefer fresh, whilst those with ‘adventurous’ values prefer processed pork products. The development of innovative pork products aiming to attend to these different groups represents interesting opportunities for the pork chain.
Deglaciation chronology and glaciomarine successions in the Malangen‐Målselv area, northern Norway

The deglaciation history of the Malangen‐Målselv fjord and valley area proximally to the Tromsø‐Lyngen (Younger Dryas) moraine at Bakkejord, Malangen, northern Norway, is reconstructed based on morphostratigraphic, lithostratigraphic and geophysical evidence, and 25 radiocarbon dates from marine shells and foraminifera. The results show that following the Skarpnes event c. 12 200 14Cyr BP, and prior to the Younger Dryas readvance, the area was deglaciated at least as far as Sandmo situated 22 km proximally to the Tromsø‐Lyngen moraine. Two moraine ridges crossing the fjord at Sandmo and buried beneath thick glaciomarine sediments are correlated with this period. The area was subsequently deglaciated between 10 300 and 9200 14Cyr BP, following the Tromsø‐Lyngen (Younger Dryas) readvance. Five ice‐front accumulations post‐dating the Tromsø‐Lyngen moraine and situated 19, 27, 42, 55 and 77 km behind it are identified and dated based on radiocarbon dates and correlation of marine limits: Målsnes (c. 10 050 14Cyr BP), Kjerresnes (c. 10 000 14Cyr BP), Solli (c. 9750 14Cyr BP), Bardufoss‐Brentmoen‐Storskogmoen (c. 9600–9700 14Cyr BP) and Alapmoen (c. 9200 Cyr BP). The largest of these, at Bardufoss‐Storskogmoen, possibly accumulated as a response to an ice advance. Fourteen dates of apparent late Allerød/Younger Dryas age (11 100–10 000 14Cyr BP), obtained from fossils in glaciomarine sediments in the Målselv valley up to 77 km proximally to the Tromsø‐Lyngen moraine, are interpreted as postdating rather than predating this moraine. Several of these are considered to be too old because of uncertain reservoir age, carbon‐dating plateaus and/or contamination. This highlights uncertainties associated with radiocarbon‐dating and the profound effect such uncertainties may have on interpreting geological events.
Wastewater Treatment Analysis, Technology and Challenges in Sweden

Wastewater treatment is an efficient technique that increases the reclamation and reuse of wastewater for other productive uses, thereby, reducing the demand for freshwater resources, conservation of aquatic habitat, and sustainable utilization of water resources. Concerns for wastewater in Sweden began in the 1930s with only mechanical treatment but efficiently implemented in the 1960s as a result of significant eutrophication observed in open waters such as the Baltic Sea. Although prevailing wastewater treatment is fairly efficient, there is need to upgrade and improve existing treatment facilities (constructed in the 1970s) to mitigate potentially degradation of hygienic conditions due to the estimated increase in Swedish population. Thus, this paper will critically analyse prevailing treatment of wastewater in Sweden, the technology used and possible challenges encountered in the process. Small scale treatment of wastewater particularly practiced for dwellings not connected to municipal treatment plant will be discussed including sludge management in Sweden. The report further presented the significant issues including regulations, challenges, health hazards and constraints associated with wastewater treatment and reclamation. In addition, background information relating to potential technology to meet future wastewater treatment in Sweden were highlighted because current wastewater treatment facilities were constructed in the 1970s to provide services to Swedish population at that time.
Tree-Invent: A Novel Multipurpose Molecular Generative Model Constrained with a Topological Tree

De novo molecular design plays an important role in drug discovery. Here, a novel generative model, Tree-Invent, was proposed to integrate topological constraints in the generation of a molecular graph. In this model, a molecular graph is represented as a topological tree in which a ring system, a nonring atom, and a chemical bond are regarded as the ring node, single node, and edge, respectively. The molecule generation is driven by three independent submodels for carrying out operations of node addition, ring generation, and node connection. One unique feature of the generative model is that the topological tree structure can be specified as a constraint for structure generation, which provides more precise control of structure generation. Combined with reinforcement learning, the Tree-Invent model could efficiently explore targeted chemical space. Moreover, the Tree-Invent model is flexible enough to be used in versatile molecule design settings such as scaffold decoration, scaffold hopping, and linker generation.
Leg 67: The Deep Sea Drilling Project Mid-America Trench transect off Guatemala

Drill cores from a transect of the Mid-America Trench off Guatemala were obtained at three sites on the oceanic Cocos plate, and at four sites on the continental Caribbean plate. An ocean sub-bottom seismometer was successfully emplaced in the deepest hole in the trench landward slope where it was left to record data after departure of the drill ship. Drilling on the Cocos plate recovered a basal chalk sequence deposited during early and mid-Miocene time, a short interval of abyssal red clay, and an upper sequence of late Miocene and younger sediment deposited within an area influenced by a terrigenous source. In the trench, a mud and sand fill less than 400,000 yr old overlies the oceanic sequence. The entire section shows no evidence of compressive deformation even at holes drilled against the trench9s landward slope. In contrast, the section cored on the trench9s landward slope 3 km from the trench axis is affected by tectonism. The section contains a Cretaceous to Pliocene claystone sequence, broken by hiatuses but in a normal stratigraphic succession that is capped by Pliocene to Quaternary hemipelagic slope deposits. Seismic records show that the section overlies probable igneous oceanic crust from which it is separated by a few hundred metres. That thickness of undrilled section is insufficient to accommodate the potential offscraped volume of oceanic sediment carried into the trench during Neogene plate convergence. At the estimated 10 cm/yr rate of convergence, much of the oceanic sediment must have been subducted rather than tectonically accreted to the Guatemalan margin. Current models for convergent margin tectonics do not satisfactorily explain the surprising occurrence of Cretaceous to Miocene mudstone at the base of this trench slope. The recovery of gas hydrates prevented drilling to some landward-dipping reflections presumed to be imbricate thrust slices at two sites near the middle of the trench landward slope.
Weak zero-knowledge beyond the black-box barrier

The round complexity of zero-knowledge protocols is a long-standing open question, yet to be settled under standard assumptions. So far, the question has appeared equally challenging for relaxations such as weak zero-knowledge and witness hiding. Protocols satisfying these relaxed notions under standard assumptions have at least four messages, just like full-fledged zero-knowledge. The difficulty in improving round complexity stems from a fundamental barrier: none of these notions can be achieved in three messages via reductions (or simulators) that treat the verifier as a black box. We introduce a new non-black-box technique and use it to obtain the first protocols that cross this barrier under standard assumptions. We obtain weak zero-knowledge for in two messages, assuming the existence of quasipolynomially-secure fully-homomorphic encryption and other standard primitives (known based on the quasipolynomial hardness of Learning with Errors), and subexponentially-secure one-way functions. We also obtain weak zero-knowledge for in three messages under standard polynomial assumptions (following for example from fully homomorphic encryption and factoring). We also give, under polynomial assumptions, a two-message witness-hiding protocol for any language ∈ that has a witness encryption scheme. This protocol is publicly verifiable. Our technique is based on a new homomorphic trapdoor paradigm, which can be seen as a non-black-box analog of the classic Feige-Lapidot-Shamir trapdoor paradigm.
Searching for reachability property in complex software systems specified through graph transformations using deep reinforcement learning

Today, model checking is one of the essential techniques in the verification of software systems. This technique can verify some properties such as reachability in which the entire state space is searched to find the desired state. However, model checking may lead to the state space explosion problem in which all states cannot be generated due to the exponential resource usage. Although the results of recent model checking approaches are promising, there is still room for improvement in terms of accuracy and the number of explored states. In this paper, using deep reinforcement learning and two neural networks, we propose an approach to increase the accuracy of the generated witnesses and reduce the use of hardware resources. In this approach, at first, an agent starts to explore the state space without any knowledge and gradually identifies the proper and improper actions by receiving different rewards/penalties from the environment to achieve the goal. Once the dataset is fulfilled with the agent's experiences, two neural networks evaluate the quality of each operation in each state, and afterwards, the best action is selected. The significant difficulties and challenges in the implementation are encoding the states, feature engineering, feature selection, reward engineering, handling invalid actions, and configuring the neural network. Finally, The proposed approach has been implemented in the Groove toolset, and as a result, in most of the case studies, it overcame the problem of state space explosion. Also, this approach outperforms the existing solutions in terms of generating shorter witnesses and exploring fewer states. On average, The proposed approach is nearly 400% better than other approaches in exploring fewer states and 300% better than the others in generating shorter witnesses. Also, on average, the proposed approach is 37% more accurate than the others in terms of finding the goals state.
DeFi: Detection and Filling of Holes in Point Clouds Towards Restoration of Digitized Cultural Heritage Models

In this paper, we propose DeFi: a novel perspective for hole detection and filling of a given deteriorated 3D point cloud towards digital preservation of cultural heritage sites. Preservation of heritage demands digitization as cultural heritage sites deteriorate due to natural calamities and human activities. Digital preservation promotes acquisition of 3D data using 3D sensor or Multi-view reconstruction. Unfortunately, 3D data acquisition finds challenges due to the limitations in sensor technology and inappropriate capture conditions, leading to formation of missing regions or holes in the acquired point cloud. To address this, we propose a pipeline consisting of detection of hole boundaries, and understanding the geometry of the hole boundaries to fill the region of the point cloud. Recent research on hole detection and filling fails to generalize on complex structures such as heritage sites, as they find challenges in differentiating between the hole boundary and non-hole boundary points. To address this, we propose to detect boundary points of point cloud and learn to classify them into "hole boundary" and "non-hole boundary" points. We generate a synthetic dataset based on ModelNet40 to learn the detection of hole boundaries. We demonstrate the results of the proposed pipeline on (i) ModelNet40 dataset, (ii) Heritage 3D models generated via photogrammetry, and compare the results with state-of-the-art methods.
Tutorial 6 : Describing Software Architecture with UML

The presence of a solid architectural vision is a key discriminator in the success or failure of a software project. This tutorial examines what software architecture is and what it is not. It discusses and illustrates how to describe architecture through a set of design viewpoints and views and how to express these views in the UML [1], in the spirit of the new IEEE Standard: Recommended practice for architectural description [2]. The tutorial shows of how architectures drive the development process and how to capture architectural design patterns using the UML. It is illustrated by several widely applicable architectural patterns in different domain.
Hidden aftershocks of the 2011 Mw 9.0 Tohoku, Japan earthquake imaged with the backprojection method

The first 25 h of the aftershock sequence following the 11 March 2011 Mw 9.0 Tohoku, Japan earthquake is investigated using a backprojection method. In total, 600 aftershocks are imaged during this time period. These aftershocks are distributed over a 500 by 300 km area and include many events in the outer rise. The backprojection events are compared with the Japan Meteorological Agency (JMA) catalogue, which is composed of earthquakes recorded by local seismic networks in Japan. Surprisingly, half of the backprojection events are not found in the JMA catalogue. These events cluster near the Japan Trench and in the outer rise and fill in gaps in the spatial distribution of the early aftershock sequence where large main shock slip is thought to have occurred. These results show that the JMA magnitude of completeness is very high near the trench following the 2011 Tohoku main shock, and earthquakes as large as magnitude 6.8 went undetected by local seismic networks.
Journal of Sound and Vibration

This work is devoted to presenting and applying a novel methodology that estimates a linear physical model, represented by full-rank mass, stiffness and damping matrices, capable of replicating the dynamic behaviour of an incomplete modal model. No hypothesis is made with respect to the damping matrix, so the procedure is applicable assuming any linear viscous damping model. It is shown that, if the number of considered modes satisfies a certain restriction with respect to the number of degrees of freedom, the problem has infinite solutions that differ in their exogenous eigenvalues. By controlling their effect on the dynamic behaviour of the model in the frequency range of interest, a proper final solution is obtained. The methodology is applied to a three-degrees-of-freedom discrete model and a discretized cantilever beam. Comparisons are made in both frequency and time domains which reveal that the methodology provides physical models that accurately replicate the dynamic behaviour of the incomplete modal model. Even for complete models, where the solvability condition is not met, the methodology manages to provide meaningful results in some situations. To prove the usefulness of the estimated models, a mass is added on one DOF of both examples to show that they reproduce the same effects as the original modified ones. Finally, in the interests of reproducibility, all models and algorithms presented in this article have been made publicly available.
Evaluation of Polar MM5 simulations of Greenland's atmospheric circulation

A complete annual cycle over the Greenland ice sheet is simulated with the Polar MM5, a mesoscale model optimized for use over extensive ice sheets. These simulations are compiled from a series of short duration (48 hour), forecast mode, simulations. The model output is compared to observations primarily from the Greenland Climate Network automatic weather station (AWS) array. The model simulations show a high degree of skill for all variables evaluated with the AWS data (pressure, temperature, water vapor mixing ratio, wind speed and direction, downwelling shortwave radiation, and net radiation) for all seasons, although the use of a fixed albedo in the Polar MM5 leads to large errors in the simulated net radiation budget over melting ice surfaces during the summer months. The modeled precipitation distribution agrees with available observations in the interior of the ice sheet but is excessive along the steep margins of the island. A discussion of possible future applications of the Polar MM5 is presented.