Miracle-dz/UniFAR-FTUs huggingface dataset:
Kinship, gender and the spiritual economy in medieval Central European Towns

ABSTRACT The present contribution starts from the debate about kinship as a social institution in medieval Europe initiated by Jack Goody's pioneering anthropological work in the 1980s and drawn upon by historians and anthropologists alike. We focus on the aspect of the allegedly systematic separation of kinship from the organization of memory of the dead brought about by the establishment of Christianity. However, throughout the European Middle Ages families did not completely cede memorial tasks to religious institutions. Rather, they re-affirmed memorial bonds to religious institutions by legal arrangements and through family members within these communities, just as kinship continued to play a key role in medieval political organization. Given their social heterogeneity medieval cities provide a rich documentation of networks across ties of family, kinship, friends, and clients that intersected with more institutionalized communities (parish churches, monasteries, hospitals). People bestowed economic benefits on these communities in return for their members' “eternal” prayer for the donators' souls. This created mutual bonds both between kin and religious communities. The ensuing forms of belonging were part of a more complex frame of social exchange, as families used the same institutions as “hubs” to corroborate social and political relations to their peers. These bonds would intersect with ties between representatives of kin groups with positions in key political organizations such as city councils. A further clue to understanding these relations is gender. Economic transactions and related memorial practices feature a considerable number of female actors underlining the salience of bilateral kin relations and practices of property devolution.
What is responsible for conformational diversity in single-crystal tetraoxazaspiroalkanes? X-Ray, DFT, and AIM approaches

The conformational mobility of large heteroatomic cycles (>6) in organic compounds studied in the liquid state is a major challenge. This is due to low energy barriers between the conformational isomers (1–2 kcal mol−1), which make it difficult to find the most important factors in their preference. Eleven single crystal tetraoxazaspirocycloalkanes are considered in this work with single-crystal X-ray diffraction, DFT, and AIM calculations. Natural bond orbital analysis at the B3LYP/6-31G(d,2p) level of theory and topological analysis of the electron density within Bader's theory of “Atoms in Molecules” showed that the tetraoxazocane cycle in spiro-adamantanetetraoxazocanes and tetraoxazaspiroalkanes possesses a twist–boat–chair conformation due to the lower interaction energy of LP(O6) → σ*(C5–N4) and the large contribution of the π-component to the C3–O2 bond. The tetraoxazocane cycle in isopropyl-methyl-tetraoxaza-spiro-tridecanes adopts a chair–chair conformation due to the higher interaction energy of LP(O6) → σ*(C5–N4) and the smaller contribution of the π-component. A key factor, which determines the large O1–O2–O6–O7 pseudo-torsion angles (102–112°) in spiro-adamantanetetraoxazocanes and tetraoxaza-spiro-alkanes, is the absence of intramolecular C–H⋯O and C–H⋯π contacts and vice versa, which provide smaller O1–O2–O6–O7 pseudo-torsion angles (0.6–4°) in isopropyl-methyl-tetraoxaza-spiro-tridecanes. The molecules of spiro-adamantanetetraoxazocanes and tetraoxazaspiroalkanes in single crystals are stabilized via C–H⋯O and C–H⋯H–C weak intermolecular interactions. The molecules of isopropyl-methyl-tetraoxaza-spiro-tridecanes are packed in crystals with C–H⋯O unusual bifurcated one-component and multicomponent contacts.
Population Fluctuation of Cotton Aphid (Aphis gossypii Glover) on Roselle Plants in Relation with Certain Biotic and Abiotic Factors

This research work was conducted to describe the relationship between the population density of the cotton aphid on roselle plants and its accompanied predators, some quantities characters of roselle plants and the main weather factors at Awlad – Sakr district, Shakira Governorate, Egypt in 2018 and 2019 growing seasons. Aphids were collected by using plant sample technique. Results indicated that A. gossypii showed seven peaks of activity, the highest one ( 1453 individuals /sample) was on the 8 th of August in the first season. In the second season A. gossypii recorded five distinct activity peaks the highest of them took place on the 23 rd of July with 5068 individuals /sample. Simple correlation, partial regression and coefficient of determination between aphid population and the aforementioned factor were evaluated. Statistical analysis results showed that these factors played a conspicuous role in detecting the activity of cotton aphid during the two investigated seasons of the study.
Individual (Co)variation in Resting and Maximal Metabolic Rates in Wild Mice

Basal metabolic rate (BMR) represents the lowest level of aerobic metabolism in a resting, postabsorptive endotherm as measured within the thermoneutral zone. By contrast, maximal metabolic rate (V˙O2max) reflects the upper limit of aerobic metabolism achieved during intensive exercise. As BMR and V˙O2max define the boundaries of the possible levels of aerobic metabolism expressed by a normothermic individual, a key question is whether BMR and V˙O2max are correlated. In the present study, we took repeated paired measurements of thermoneutral resting metabolic rate (RMRt) and V˙O2max on 165 white-footed mice (Peromyscus leucopus). Over a single summer (May–October), repeatability (R ± SE) was low but statistically significant (P<0.05) for both RMRt and V˙O2max (R=0.15±0.08 for RMRt; R=0.27±0.12 for V˙O2max). Willingness to run during the forced-exercise trials was also significantly repeatable (R=0.16±0.08). At the residual level (within individual), RMRt and V˙O2max tended to be positively correlated (re=0.23±0.11, P=0.051), suggesting the presence of correlated phenotypic plasticity. By contrast, RMRt and V˙O2max were significantly negatively correlated at the among-individual level (rind=−0.84±0.40). To the extent that variation in RMRt reflects variation in BMR, the negative among-individual correlation does not corroborate the idea that a costly metabolic machinery is needed to support a high V˙O2max. Future research should investigate the (genetic) relationship between RMRt (and BMR) and other energetically expensive behaviors and activities to better understand how energy is allocated within individuals.
Pairing automated mark–recapture and social network models to explore the effects of landscape configuration on hummingbird foraging patterns

Landscape changes can alter pollinator movement and foraging patterns which can in turn influence the demographic processes of plant populations. We leveraged social network models and four fixed arrays of five hummingbird feeders equipped with radio frequency identification (RFID) data loggers to study rufous hummingbird (Selasphorus rufus) foraging patterns in a heterogeneous landscape. Using a space-for-time approach, we asked whether forest encroachment on alpine meadows could restrict hummingbird foraging movements and impede resource discovery. We fit social network models to data on 2221 movements between feeders made by 29 hummingbirds. Movements were made primarily by females, likely due to male territoriality and early migration dates. Distance was the driving factor in determining the rate of movements among feeders. The posterior mean effects of forest landscape variables (local canopy cover and intervening forest cover) were negative, but with considerable uncertainty. Finally, we found strong reciprocity in hummingbird movements, indicative of frequent out and back movements between resources. Together, these findings suggest that reciprocal movements by female hummingbirds could help maintain bidirectional gene flow among nearby subpopulations of ornithophilous plants; however, if the distance among meadows increases with further forest encroachment, this may limit foraging among progressively isolated meadows.
The influence of electrode spacing on the performance of bioretention cell coupled with MFC

In order to explore the influence of electrode spacing on the performance of the enhanced bioretention system, four bioretention cells with microbial fuel cell (BRC–MFC) systems with different electrode spacing were designed, and the effect of electrode spacing on system performance was revealed by analysing its water treatment capacity and electricity production efficiency. The results showed that BRC–MFC had good water treatment capacity and could produce electricity simultaneously. Compared with other BRC–MFC systems with spacing, the BRC3 system (with an electrode spacing of 30 cm) had significant water treatment capacity under different organic loads, especially under high organic load (C/N = 10) operation, COD removal rate was as high as 98.49%, NH4+−N removal rate was as high as 97%, and it had a higher output voltage of 170.46 ± 6.17 mV. It could be seen that proper electrode spacing can effectively improve the water treatment capacity of the BRC–MFC system. This study provided a feasible method for improving the performance of the BRC–MFC system, and revealed the relevant mechanism. A proper electrode spacing with sufficient carbon sources could effectively improve the water treatment capacity of the BRC–MFC system.
Extraction of urban built-up area based on the fusion of night-time light data and point of interest data

The accurate extraction of urban built-up areas is an important prerequisite for urban planning and construction. As a kind of data that can represent urban spatial form, night-time light data has been widely used in the extraction of urban built-up areas. As one of the geographic open-source big data, point of interest (POI) data has a high spatial coupling with night-time light data, so researchers are beginning to explore the fusion of the two data in order to achieve more accurate extraction of urban built-up areas. However, the current research methods and theoretical applications of the fusion of POI data and night-time light data are still insufficient compared with the dramatically changing urban built-up areas, which needed to be further supplemented and deepened. This study proposes a new method to fuse POI data and night-time light data. The results before and after data fusion are compared, and the accuracy of urban built-up area extracted by different data and methods is analysed. The results show that the data fusion can avoid the shortage of single data and effectively improve the extraction accuracy of urban built-up areas, which is greatly helpful to supplement the study of data fusion in urban built-up areas, and also can provide decision-making guidance for urban planning and construction.
Ancient DNA reveals multiple origins and migration waves of extinct Japanese brown bear lineages

Little is known about how mammalian biogeography on islands was affected by sea-level fluctuations. In the Japanese Archipelago, brown bears (Ursus arctos) currently inhabit only Hokkaido, the northern island, but Pleistocene fossils indicate a past distribution throughout Honshu, Japan's largest island. However, the difficulty of recovering ancient DNA from fossils in temperate East Asia has limited our understanding of their evolutionary history. Here, we analysed mitochondrial DNA from a 32 500-year-old brown bear fossil from Honshu. Our results show that this individual belonged to a previously unknown lineage that split approximately 160 Ka from its sister lineage, the southern Hokkaido clade. This divergence time and fossil record suggest that brown bears migrated from the Eurasian continent to Honshu at least twice; the first population was an early-diverging lineage (greater than 340 Ka), and the second migrated via Hokkaido after approximately 160 Ka, during the ice age. Thus, glacial-age sea-level falls might have facilitated migrations of large mammals more frequently than previously thought, which may have had a substantial impact on ecosystem dynamics in these isolated islands.
A Comprehensive Survey of Privacy-preserving Federated Learning

The past four years have witnessed the rapid development of federated learning (FL). However, new privacy concerns have also emerged during the aggregation of the distributed intermediate results. The emerging privacy-preserving FL (PPFL) has been heralded as a solution to generic privacy-preserving machine learning. However, the challenge of protecting data privacy while maintaining the data utility through machine learning still remains. In this article, we present a comprehensive and systematic survey on the PPFL based on our proposed 5W-scenario-based taxonomy. We analyze the privacy leakage risks in the FL from five aspects, summarize existing methods, and identify future research directions.
On the Use of Intelligent Models towards Meeting the Challenges of the Edge Mesh

Nowadays, we are witnessing the advent of the Internet of Things (IoT) with numerous devices performing interactions between them or with their environment. The huge number of devices leads to huge volumes of data that demand the appropriate processing. The “legacy” approach is to rely on Cloud where increased computational resources can realize any desired processing. However, the need for supporting real-time applications requires a reduced latency in the provision of outcomes. Edge Computing (EC) comes as the “solver” of the latency problem. Various processing activities can be performed at EC nodes having direct connection with IoT devices. A number of challenges should be met before we conclude a fully automated ecosystem where nodes can cooperate or understand their status to efficiently serve applications. In this article, we perform a survey of the relevant research activities towards the vision of Edge Mesh (EM), i.e., a “cover” of intelligence upon the EC. We present the necessary hardware and discuss research outcomes in every aspect of EC/EM nodes functioning. We present technologies and theories adopted for data, tasks, and resource management while discussing how machine learning and optimization can be adopted in the domain.
Context-aware Retrieval-based Deep Commit Message Generation

Commit messages recorded in version control systems contain valuable information for software development, maintenance, and comprehension. Unfortunately, developers often commit code with empty or poor quality commit messages. To address this issue, several studies have proposed approaches to generate commit messages from commit diffs. Recent studies make use of neural machine translation algorithms to try and translate git diffs into commit messages and have achieved some promising results. However, these learning-based methods tend to generate high-frequency words but ignore low-frequency ones. In addition, they suffer from exposure bias issues, which leads to a gap between training phase and testing phase. In this article, we propose CoRec to address the above two limitations. Specifically, we first train a context-aware encoder-decoder model that randomly selects the previous output of the decoder or the embedding vector of a ground truth word as context to make the model gradually aware of previous alignment choices. Given a diff for testing, the trained model is reused to retrieve the most similar diff from the training set. Finally, we use the retrieval diff to guide the probability distribution for the final generated vocabulary. Our method combines the advantages of both information retrieval and neural machine translation. We evaluate CoRec on a dataset from Liu et al. and a large-scale dataset crawled from 10K popular Java repositories in Github. Our experimental results show that CoRec significantly outperforms the state-of-the-art method NNGen by 19% on average in terms of BLEU.
Optimisation of cutting parameters and surface deformation during thin steel sheets plasma processing using Taguchi approach

Plasma machining was investigated for suitability to cut thin sheets and the quality obtained was assessed. The aim of this research was to analyse the impact of the heat generated from plasma cutting on thin sheet surface deformation and heat affected zones. Plasma cutting was assumed to be noneffective for processing thin material, this technology was known primely for cutting medium to thick plates. Tremendous work was performed previously to improve the quality. However, there are no scientific publications assessed the effect of the plasma heat on thin material under 1 mm and optimised optimise the process to reduce the phenomena resulted to their minimal. The traditional cutting methods were found to be limited and time consuming. This research can be beneficial for vehicle convertors such as wheelchair accessible vehicles or similar industries where conventional cutting methods are still predominant. Therefore, an automated plasma cutter if properly optimised would be an effective solution. CNC Plasma cutter with an automated torch height adjustment was used for this experiment to process a 0.6 mm thick deep drawing cold rolled DCO1 steel grade material. Tests were carried out varying the plasma parameters speed, pressure and intensity, the quality obtained was assessed. Three-dimensional Triplescan Atos model was used to measure the maximum surface deformation. Samples were sectioned, mounted, polished, mirrored and etched with 5% Nital acid to expose the material grains. Results were gathered on a tables, then Taguchi method and Analysis of Variance were used to optimise and analyse the parameters. Results showed an effective cut for thin materials. The optimal values obtained were 8000 mm/min, pressure 70 psi and Intensity 25 A for sheet deformation whereas heat affected zones was cutting speed 8500 mm/min, pressure 80 psi and Intensity 30 A. Cutting speed and intensity had the highest impact on deformation however heat affected zones was influenced mainly by the cutting speed. The study suggested also that a mathematical model can be constructed to predict the response for both phenomena and assess the relationship strength, the method used was least square error, the tests showed that the models fit adequately and can be trusted to predict new values. Lastly, a vehicle chassis was used for the test, the results showed an effective cutting on painted material, no second processing was required. Sealant under the material required removal on plasma pathway to avoid excess smoke or fire generation. An estimation was made for the underbody chassis cut out processing time and it was found that automated plasma can reduce the cycle time to just above 40 min.
Osteoarthritis-Related Knee Pain Treated With Genicular Artery Embolization: A Systematic Review and Meta-analysis

Background: Genicular artery embolization (GAE) is an innovative technique that has been investigated as a supplementary treatment method for chronic pain secondary to knee osteoarthritis (OA). Purpose: To evaluate the current evidence on the effectiveness and safety of GAE for OA-related knee pain. Study Design: Systematic review; Level of evidence, 4. Methods: A systematic literature search was conducted in the PubMed, Web of Science, EMBASE, and Scopus databases to identify studies related to knee OA treated with GAE. Treatment agents were categorized as Embozene, imipenem/cilastatin, resorbable microspheres, and polyvinyl alcohol. The main outcomes were the mean difference (MD) in pre- and postembolization pain based on the visual analog scale (VAS) or the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores as well as changes in the need for pain medication. Random- and fixed-effects models were applied for data analysis. Results: Of 379 initially inspected publications, 11 (N = 225 patients; 268 knees) were included in the final review. The quality of the studies was fair in 8 and poor in 3—categorized according to the National Institutes of Health quality assessment tool. Overall, 119, 72, 13, and 21 patients were treated with imipenem/cilastatin, Embozene, resorbable microspheres, and polyvinyl alcohol, respectively. Symptomatic improvement was reported in all studies. The pooled effect size, characterized by MD, showed a significant improvement in the VAS and WOMAC pain scores, with better functional status after GAE. Pre- versus postembolization MDs in VAS scores ranged from 32 within the first week to 58 after a 2-year follow-up (equivalent to 54% and 80% improvement, respectively). There was a similar trend in the overall WOMAC scores, with MDs ranging from 28.4 to 36.8 (about 58% and 85% improvement, respectively). GAE resulted in a decreased need for pain medication for knee OA, with a 27%, 65%, and 73% decline in the number of patients who used opioids, nonsteroidal anti-inflammatory drugs, and intra-articular hyaluronic acid injection, respectively (P < .00001 for all). No significant difference between embolic agents was seen with regard to post-GAE pain reduction. No severe or life-threatening complications were reported. Conclusion: OA treated by GAE using different embolic particles can be considered generally safe, with good efficacy and no reported serious complications.
The spontaneous theoreticians: How evaluators build and revise their knowledge of programs through experience

What exactly do evaluators learn about programs through experience and how? We chose a constructivist framework to investigate the structure of evaluators’ program-related knowledge, namely the form, content, and origins of their expressed theories. In this context, we complemented a Piagetian theory of learning with new developments offered by “probabilistic” (or “Bayesian”) models of learning. We conducted “explicitation” interviews with nine experienced practitioners, some specializing in the education or agri-environment sectors and some generalists. After examining the form and content of their program-related knowledge, we examine its development through experience but also through contact with researchers and readings. In conclusion, we discuss our study’s strengths and limitations, as well as the implications of our results for evaluation training and teaching.
Numerical homogenization beyond scale separation

Numerical homogenization is a methodology for the computational solution of multiscale partial differential equations. It aims at reducing complex large-scale problems to simplified numerical models valid on some target scale of interest, thereby accounting for the impact of features on smaller scales that are otherwise not resolved. While constructive approaches in the mathematical theory of homogenization are restricted to problems with a clear scale separation, modern numerical homogenization methods can accurately handle problems with a continuum of scales. This paper reviews such approaches embedded in a historical context and provides a unified variational framework for their design and numerical analysis. Apart from prototypical elliptic model problems, the class of partial differential equations covered here includes wave scattering in heterogeneous media and serves as a template for more general multi-physics problems.