Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic Construction of Neural Forms for Solving Partial Differential Equations Inside Rectangular Domains, Subject to Initial, Boundary and Interface Conditions

A systematic approach is developed for constructing proper trial solutions to Partial Differential Equations (PDEs) of up to second order, using neural forms that satisfy prescribed initial, boundary and interface conditions. The spatial domain considered is of the rectangular hyper-box type. On each face either Dirichlet or Neumann conditions may apply. Robin conditions may be accommodated as well. Interface conditions that induce discontinuities, have not been treated to date in the relevant neural network literature. As an illustration a common problem of heat conduction through a system of two rods in thermal contact is considered.
Why some local governments choose not to free-ride when undergoing boundary reform: a study of two merger cases in Poland

ABSTRACT One of the side effects of municipal territorial reforms is the common-pool problem. The problem arises when the costs of an activity that benefits a small entity are borne by a larger entity. A review of existing empirical studies suggests that although the common-pool problem has been identified in all investigated cases, it has not as yet been sufficiently analysed and understood. This article focuses on two voluntary mergers in Poland. The authors test the impact of the merger decision on the pre-merger level of capital spending and debt. The analysis is based on a quasi-experimental design using Synthetic Control method. The paper identifies factors explaining why the behaviour of the analysed merging municipalities differs from the results of earlier studies. The most important finding is that the mechanism preventing common resources hoarding is effective when local rules are applied to the merger.
Isolation, characterization and expression of an elongation factor 1α gene in potato (Solanum tuberosum) cell cultures

Abstract Using a differential display (DDRT‐PCR) approach to screen genes involved in response to osmotic stress, we isolated six cDNA clones from potato cell cultures. One of these, clone #54, is a member of the gene family encoding the α‐subunit of translation elongation factor 1 (EF‐1α). After sequencing, this clone showed a deduced amino acid sequence of 447 residues. Southern blot analysis revealed that this EF‐1α is a member of a family consisting of at least nine genes. The expression of EF‐1α increased upon osmotic stress mediated by polyethylene glycol (PEG) but was unaffected by abscisic acid (ABA) treatment. Salt also increased EF‐1α expression but with a different kinetics. These results indicate that we cloned an EF‐1α in potato which is ABA responsive, independent of osmotic stress. Abbreviations: DDRT‐PCR, differential display reverse transcriptase‐polymerase chain reaction; PEG, polyethylene glycol; RACE, rapid amplification of cDNA ends; RT‐PCR, reverse transcriptase‐polymerase chain reaction
The Mediterranean Endemic New genus Felicinia (Halymeniales, Rhodophyta) Recognized by a Morphological and Phylogenetic Integrative Approach

Abstract Recently, DNA phylogenies resulted in the transfer of some species of the halymeniacean genus Aeodes, namely A. orbitosa and A. ulvoidea, to the genus Pachymenia leaving the former supposedly as a monotypic genus based on the type species, A. nitidissima. Nevertheless, that work overlooked the presence of A. marginata, a red foliaceus alga endemic to the Mediterranean Sea with a convoluted nomenclatural history. In the present study, we provided a thorough description of A. marginata based on both anatomical and molecular data and inferred its phylogenetic relationships among halymeniacean genera using both chloroplastic (rbcL) and nuclear genes (LSU). Based on our data, A. marginata allied with Halymenia, Cryptonemia, and associated genera rather than with the generitype A. nitidissima, and presented a unique set of characters deserving the status of genus within the Halymeniaceae. Therefore, we proposed the new genus Felicinia based on Felicinia marginata comb. nov. A description of the multiaxial vegetative of F. marginata construct was provided, highlighting a unique characteristic among red algae: the presence, in the medulla, of peculiar oblique multicellular filaments connecting periclinal filaments. These filaments are produced secondarily as branches from axial filaments and are possibly homologous to the anticlinal filaments observed in the medulla of Halymenia.
Antiulcer Effect of Mammalian Lignan Precursors from Flaxseed

Abstract The antiulcer potential of the crude extract of lignans from flaxseed (Linum usitatissimum. Linn, Linaceae) was evaluated and compared against β -carotene in NSAID-induced gastric ulcers in the Wistar rat model. The isolated stomach tissue was studied for percentage ulcer index and reduced glutathione (GSH) content. The crude extract of lignans exhibited significant protection and better recovery (p < 0.05) against ulcer formation as well as in GSH content maintenance. Further, the antiulcer effect of the crude extract of lignans was comparable with that of standard β -carotene.
Characteristics of In Vitro Fermentation and Nutrient Digestibility of Ration Supplemented with Different Level of Soybean Oil Calcium Soap

The in vitro experiment was aimed to evaluate the effect of soybean oil calcium soap (CaS-soybean) supplementation in ration on fermentability characteristics, microbial population and nutrient digestibility by using rumen fluid of Bali cattle. The experiment was arranged in a completelyrandomized block design with 4 different ration treatments with 3 replicates. The ration treatments were R1: 40% native grass (NG) + 60% concentrate (C), R2 (40% NG + 60% C containing 2.5% CaS-soybean), R3: (40% NG + 60% C containing 5.0% CaS-soybean) and R4 (40% NG + 60% C containing 7.5% CaS-soybean). The measured variables were pH, NH3-N, total volatile fatty acids, total bacteria and protozoa (microbial populations), dry matter and, and organic matter digestibility. The datawere analyzed by using Analysis of Variance and the differences between treatments were examined with Duncan’s Multiple Range Test. The experimental results showed that the different feed treatments did not have any significant effect on pH, ammonia (NH3-N) concentration, total bacteria, protozoa population, dry matter, and organic matter digestibility. However, the treatments significantly affect the total volatile fatty acids (VFA) production. Ration with 7.5% CaS-soybean (R4) had the highest VFA concentration compared to R1 (Control), R2 (control ration + 2.5% CaS-soybean and R3 (control ration contains 5% CaS-soybean). Feed treatment supplemented with 5.0% CaS-soybean (R3) had a higher total VFA concentrationcompare to control rations (R0). In conclusion, supplementation of the different levels of CaS-soybean within concentrate created thenormal of in vitro fermentation characteristics and the total production of VFA.
Dispersal Syndromes in North American Ephedra

Ephedra (Gymnosperma, Gnetales, Ephedraceae) includes 13 species in the arid American Southwest that have three morphological types of propagules. We performed field and laboratory experiments on five species (E. torreyana, E. antisyphilitica, E. viridis, E. funerea, and E. nevadensis) that represent the three morphological types (dispersal syndromes) and two intermediate forms. Ephedra torreyana has large, winged cone bracts and small seeds that are largely ignored by animals and that are dispersed by the wind. Ephedra antisyphilitica has succulent cone bracts that are eaten by birds that disperse the seeds in their feces. Ephedra viridis has large, conspicuous seeds that are attractive to some rodents, which gather the seeds and scatter hoard them in soil. Ephedra funerea and E. nevadensis are also dispersed by seed‐caching rodents but share traits with wind‐dispersed and bird‐dispersed species, respectively. Most North American species of Ephedra are dispersed by seed‐caching rodents, and this mode of dispersal is not represented in Ephedra from other continents (i.e., arid portions of South America, North Africa, Europe, Asia), perhaps because of a more diverse assemblage of seed‐caching rodents in North America than in these other regions.
Leveraging volunteer fact checking to identify misinformation about COVID-19 in social media

the type of misinformation. Our strategy uncovered tweets containing misinformation about COVID-19 for both topics with high signal-to-noise ratio (SNR) (i.e., the fraction of tweets containing misinformation) compared to naive keyword-based search that inspects misinformation in a set of tweets containing context-specific keywords. While our strategy seems to work well for the topics we studied, more research is needed to assess how it generalizes to other cases. We plan to test the performance of our strategy more comprehensively for diverse types of misinformation in future research.
A Step Towards a Better Understanding of Pain Phenotypes: Latent Class Analysis in Chronic Pain Patients Receiving Multimodal Inpatient Treatment

Purpose The number of non-responders to treatment among patients with chronic pain (CP) is high, although intensive multimodal treatment is broadly accessible. One reason is the large variability in manifestations of CP. To facilitate the development of tailored treatment approaches, phenotypes of CP must be identified. In this study, we aim to identify subgroups in patients with CP based on several aspects of self-reported health. Patients and Methods A latent class analysis (LCA) was carried out in retrospective data from 411 patients with CP of different origins. All patients experienced severe physical and psychosocial consequences and were therefore undergoing multimodal inpatient pain treatment. Self-reported measures of pain (﻿visual analogue scales for pain intensity, frequency, and impairment; Pain Perception Scale), emotional distress (Patient Health Questionnaire, PHQ-9; Generalized Anxiety Disorder Scale, GAD-7) and physical health (Short Form Health Survey; SF-8) were collected immediately after admission and before discharge. Instruments assessed at admission were used as input to the LCA. Resulting classes were compared in terms of patient characteristics and treatment outcome. Results A model with four latent classes demonstrated the best model fit and interpretability. Classes 1 to 4 included patients with high (54.7%), extreme (17.0%), moderate (15.6%), and low (12.7%) pain burden, respectively. Patients in class 4 showed high levels of emotional distress, whereas emotional distress in the other classes corresponded to the levels of pain burden. While pain as well as physical and mental health improved in class 1, only the levels of depression and anxiety improved in patients in the other groups during multimodal treatment. Conclusion The specific needs of these subgroups should be taken into account when developing individualized treatment programs. However, the retrospective design limits the significance of the results and replication in prospective studies is desirable.
Superlinear and Bandwidth Friendly Geo-replication for Store-and-forward Systems

To keep internet based services available despite inevitable local internet and power outages, their data must be replicated to one or more other sites. For most systems using the store-and-forward architecture, data loss can also be prevented by using end-to-end acknowledgements. So far we have not found any sufficiently good solutions for replication of data in store-and-forward systems without acknowledgements and with geographically separated system nodes. We therefore designed a new replication protocol, which could take advantage of the lack of a global order between the messages and the acceptance of a slightly higher risk for duplicated deliveries than existing protocols. We tested a proof-of-concept implementation of the protocol for throughput and latency in a controlled experiment using 7 nodes in 4 geographically separated areas, and observed the throughput increasing superlinearly with the number of nodes up to almost 3500 messages per second. It is also, to the best of our knowledge, the first replication protocol with a bandwidth usage that scales according to the number of nodes allowed to fail and not the total number of nodes in the system.
Regulation of Growth and Mortality in Larval Bluegills: Implications for Juvenile Recruitment

Abstract Factors related to growth and survival of 10-d cohorts of larval bluegills Lepomis macrochirus were examined in two small impoundments via daily growth increments on otoliths. Successful spawning occurred from April through September, producing peak larval densities greater than 360 fish/m3. Larval bluegill density was negatively correlated with zooplankton density in both ponds, suggesting that larvae reduced zooplankton abundance via predation. Several variables were related to larval growth and mortality. Cohorts whose larval densities were low tended to have faster growth and higher survival than cohorts with high larval densities. The mechanism responsible for this density-dependent relation was not clear in all instances; however, some evidence suggested that control occurred via intraspecific competition for zooplankton. Relative survival of larval bluegills to the juvenile stage was negatively correlated with limnetic larval fish density; however, no relations were detected between larval.
Habitat Determinants of Woodpecker Abundance and Species Richness in Sub-Himalayan Dipterocarp Forests of North-West India

Abstract. Ecological impacts of habitat change on woodpeckers remain largely unstudied in regions other than Europe and North America. The sub-Himalayan sal Shorea robusta forests of northwest India have 17 woodpecker species, and a history of management-induced habitat modification. We studied how habitat parameters affect woodpeckers at a community level (viz. total abundance and species richness) as well as at individual species level. We assessed woodpecker abundance, species richness and described habitat features at 8 sites representing a gradient of structure and composition in a sal-dominated landscape. We surveyed each site in 2-km-long transects 20 times over breeding and non-breeding seasons and evaluated habitat characteristics in 10 circular and belt plots. We analysed woodpecker abundance, species richness, and abundance of individual species as functions of habitat variables and season. Woodpecker encounter rates and mean species richness, respectively, ranged from 1.5 to 10.0 birds/km and 1.7 to 6.9 species per survey at individual sites. Distance-based estimates of densities for the most frequently-observed species were also obtained. Basal area (large trees) and density of snags positively influenced total woodpecker abundance and species richness, with snags being more important during breeding season. Basal area was important for Greater Flameback Chrysocolaptes lucidus, Grey-faced Woodpecker Picus canus, Fulvous-breasted Woodpecker Dendrocopos macei and Lesser Yellownape Picus chlorolophus. Snags, tree density, tree diameter and termitarium density appeared to affect Greycapped Pygmy Woodpecker Dendrocopos canicapillus, Black-rumped Flameback Dinopium benghalense, Himalayan Flameback Dinopium shorii and Streak-throated Woodpecker Picus xanthopygaeus. Hence, for the conservation of native woodpecker communities in sal forests, it is necessary to retain large trees and standing dead wood.
A Robust Deep Learning-Based Fault Diagnosis Method for Rotating Machinery

In the recent years, intelligent data-driven faultdiagnosis methods on gearboxes have been successfully developedand popularly applied in the industries. Currently, most ofthe machine learning techniques require that the training andtesting data are from the same distribution. However, thisassumption is difficult to be met in the real industries, sincethe gearbox operating conditions usually change in practice,which results in significant data distribution gap and diagnosticperformance deteriorations in applying the learned knowledgeon the new conditions. This paper proposes a deep learning-based domain adaptation method to address this issue. Theraw current signals are directly used as the model inputs fordiagnostics, which are easy to collect in the real industries andfacilitate practical applications. The maximum mean discrepancymetric is introduced to the deep neural network, the optimizationof which guarantees the extraction of generalized machineryhealth condition features across different operating conditions.The experiments on a real-world gearbox condition monitoringdataset validate the effectiveness of the proposed method, whichoffers a promising tool for cross-domain diagnosis in the realindustries.
A Multi-Vehicle Control Framework With Application to Automated Valet Parking

We introduce a distributed control method for coordinating multiple vehicles in the framework of an automated valet parking (AVP) system. The control functionality is distributed between an infrastructure server, called parking area management (PAM) system, and local autonomous vehicle control units. Via a vehicle-to-infrastructure (V2I) communication interface, model predictive control (MPC) decisions of the vehicles are shared with the coordination unit in the PAM. This unit in turn computes a coupling feedback which is shared with the vehicles. The control system is integrated in an automated test-system to cope with the high test requirements and short development cycles of highly automated systems. Evaluations conducted with the test-system show the functionality of the proposed distributed control method for multi-vehicle coordination. Results indicate safe coordination, and an efficiency increase compared to an uncoordinated method in an AVP simulation environment.
Interactive Machine Learning: Strategies for live performance using Electromyography

We present use of the electromyogram (EMG) for sensing musical gesture and discuss interactive machine learning for designing complex muscle-music inter- actions. We propose a signal flow for musical interaction with body movement sensed by EMG and other sensing modalities, feature extraction, and interactive machine learning that result in the manipulation of sound synthesis parame- ters. We discuss ways to capture the EMG for musical use including electrode placement and the use of multiple EMG channels. Techniques for extracting meaningful data and features from electromyographic signals are discussed. We present a composite feature, a multi-channel EMG vector sum. Signal pro- cessing and machine learning are demonstrated. We frame classification and regression as cases of recognising and mapping. We finish by providing a series of resources for musicians wishing to work with the techniques presented here. These tools are free and open source, and can be implemented easily in new applications, projects or products.
Understanding Chinese Residents’ Waste Classification from a Perspective of Intention–Behavior Gap

It remains uncertain as to whether people who support waste classification end up transforming such environmental initiation into reality. Thus, to investigate the intention and actual behavior of Chinese residents on waste classification and the influencing factors, this study integrated the theory of planned behavior (TPB) and norm activation model (NAM), and extended them by adding external information factors, namely information publicity type and information quality. A questionnaire survey was conducted in mainland China, and the primary data from 349 individuals were analyzed by partial least squares structural equation modeling (PLS-SEM) to verify the model. The conclusions confirmed that personal norm was a major predictor of residents’ waste classification intention, and there exists a gap between Chinese residents’ waste classification intentions and actual behaviors. Furthermore, strategies such as moral education and information publicity are important in policy implementation. These findings are helpful for Chinese policymakers in promoting and planning waste classification, and also provide experiences to other countries for combating similar waste problems in their metropolises.
Mid-Term Effects of Pulmonary Rehabilitation on Cognitive Function in People with Severe Chronic Obstructive Pulmonary Disease

Purpose Cognitive dysfunction is a common impairment associated with COPD. However, little is known about 1) its prevalence among those subjects referred for pulmonary rehabilitation (PR), 2) how it may affect the benefit of PR, 3) whether PR improves cognitive function and 4) whether cognitive dysfunction affects the usability of telehealth technology usually used to deliver in-home PR. Patients and Methods ﻿Fifty-six subjects with stable COPD (54% females, mean age 62 years (SD 9) and median FEV1 0.9 L (IQR 0.7 to 1.1)) participated in this multicenter observational study and performed 24 sessions of PR. The Montreal Cognitive Assessment ﻿tool (MoCA) was used to assess the occurrence of mild cognitive dysfunction (using a screening cutoff <26) at baseline, completion of PR and 3 months of follow-up. Results Mild cognitive dysfunction was found in 41 subjects (73% [95% CI: 60 to 83%]). The MoCA score significantly improved following PR for those people with baseline mild cognitive dysfunction (p<0.01). There was no significant difference in clinical outcomes between those people with or without mild cognitive dysfunction following PR nor in the proportion of subjects who were autonomous in using the telemonitoring system (83% compared with 71%, p=0.60). Conclusion Mild cognitive dysfunction is highly prevalent among those people with COPD referred for PR but does not affect the benefits of PR nor the usability of a telemonitoring system. PR may improve short- and mid-term cognitive function for those people who experience mild cognitive dysfunction at the time they are referred to PR.
On the Presence of Pipistrelle Bats (Pipistrellus and Hypsugo; Chiroptera: Vespertilionidae) in Sardinia

Islands are biodiversity hotspots, often containing numerous endemic species. This makes them also hotspots for conservation. Within the Mediterranean region, Sardinia is known for its comparatively high degree of endemism, including cryptic diversity. In this paper we aim to elucidate the variability of pipistrelles (Pipistrellus and Hypsugo) on Sardinia. More specifically, we ask which species occur on Sardinia and we describe the geographic affiliations of these evolutionary lineages. We sequenced ca. 560 bp of the 16S rRNA gene from 36 pipistrelle specimens representing 17 localities from all major parts of Sardinia. For comparison we added samples from the entire Mediterranean region as well as sequences stored at GenBank. We constructed Bayesian phylogenetic trees and minimum spanning networks to identify which species occur on Sardinia and to infer their genetic affiliation to lineages occurring throughout the Mediterranean and the Canary Islands. We identified five pipistrelle lineages on Sardinia: Pipistrellus pipistrellus (haplolineage II), P. pygmaeus, P. kuhlii/desertii, Hypsugo savii s.str. and H. cf. darwinii. Colonization of Sardinia occurred at different times from different geographical sources, namely Europe and Africa. Some lineages may have invaded Sardinia recently. The Sardinian H. cf. darwinii may be endemic to the island. Our results highlight the importance of Sardinia as a major Mediterranean hotspot for bat biodiversity. The island harbours a pipistrelle diversity that is higher than that on any other Mediterranean island. Lying geographically at the interface between Europe and Africa, Sardinia combines elements from both continents.