Miracle-dz/UniFAR-FTUs huggingface dataset:
Update on the geographic distribution of the critically endangered Urothemis edwardsii (Selys, 1849) (Odonata: Libellulidae) in northeastern Algeria

Summary. Assessing temporal changes of the distribution of threatened species is paramount for effective management. Threatened species are sensitive to environmental changes and can be extirpated rapidly due to climatic and anthropogenic effects. Here, we monitor the distribution of the locally critically endangered Urothemis edwardsii in northeastern Algeria where the species has been recovering during the last decade after being restricted to a single locality since the 1990s. During the flight seasons in 2018, 2019, and 2021, we conducted field surveys recording the number of males, females, and breeding pairs across 15 sites in northeast Algeria (El Taref province). We found the species at seven sites; reproduction was confirmed at four. In two of the sites, the species was newly recorded but showed no signs of reproduction. We confirmed the maintenance of the reproductive populations that were recently discovered. While the local conservation status of the species is better than that in the 1990s, there are still different threats that need to be addressed and conservation measures that should be implemented or reinforced to ensure maintenance as well as future expansion of the species.
Determining the Environmental Benefits of Ultra High Performance Concrete as a Bridge Construction Material

Ultra High Performance Concrete (UHPC) is a material that is attracting attention in the construction industry due to the high mechanical strength and durability, leading to structures having low maintenance requirements. The production of UHPC, however, has generally higher environmental impact than normal strength concrete due to the increased demand of cement required in the concrete mix. What is still not sufficiently investigated, is if the longer lifetime, slimmer construction and lower maintenance requirements lead to a net environmental benefit compared to standard concrete bridge design. This study utilizes life cycle assessment (LCA) to determine the lifetime impacts of two comparable highway crossing footbridges spanning 40 meters, designed respectively with UHPC and normal strength concrete. The results of the study show that UHPC is an effective material for reducing lifetime emissions from construction and maintenance of long lasting infrastructure, as the UHPC design outperforms the normal strength concrete bridge in most impact categories.
Studying dual-sensor time-series remote sensing data for Dalbergia sissoo mapping in a Lesser Himalayan area

Abstract. Information about species mapping is an essential approach for the management of forests and sustainable practices of conservation. Remote sensing data have proven to be an asset for the assessment of the spatial distribution of species over time. We used time-series data from a single sensor (PlanetScope) and dual-sensor (PlanetScope with Sentinel-2) to map Dalbergia sissoo, a timber species, found on both sides of the Jakhan river in Dehradun district of Lesser Himalaya. The dimensionality of the temporal images was reduced by normalized difference vegetation index (NDVI) and class-based sensor independent NDVI (CBSI-NDVI). Separability analysis was conducted to find optimal dates of the data set using three measures of separability, and Euclidean distance was found to be the best measure of separability for both the indices. Due to limitations of the classifiers in handling mixed pixels, a fuzzy-based modified possibilistic c-means (MPCM) algorithm was tested to extract a single class, i.e., Shisham (Dalbergia sissoo) tree. We used the conventional mean and individual sample as mean (ISM) as training parameter concepts in the MPCM supervised classification approach. We found that the ISM approach was able to handle the heterogeneity within the class for both vegetation indices. It was seen that PlanetScope data were able to spatially map the target class in a better way, whereas combined data of PlanetScope and Sentinel-2 helped to reduce the spectral overlap between target and nontarget classes. An accuracy assessment was performed using mean membership difference, variance, and entropy where variance and entropy showed that NDVI-based ISM approach outperformed the CBSI-NDVI-based approach. Both single-and dual-sensor time-series data showed good classification results for single species extraction.
INFLUÊNCIA DO TEOR DE FIBRAS DE POLIPROPILENO NO COMPORTAMENTO HIDRÁULICO DE SOLOS NÃO SATURADOS

: The inclusion of polypropylene fibers alters the hydromechanical behavior of the soil. In view of this, the present study studies the influence of the inclusion of polypropylene fibers to the soil in their hydromechanical behavior from the experimental program, which consisted of conducting geotechnical characterization tests and paper tests filter to obtain the retention curves from the adjustment models of Fredlund and Xing (1994) and Gitirana and Fredlund (2004) for a sandy natural soil and soil-fiber mixtures, with different levels of polypropylene fibers. Based on the retention curves of the studied mixtures, the influence of polypropylene fiber content on the hydraulic behavior of unsaturated soil was evaluated. From the results, the transition from the unimodal retention curve to bimodal was observed with the addition of polypropylene fibers, suggesting that the inclusion of the fibers altered the soil structure. In addition, it was possible to identify that the retention curves for the samples with addition of 0.25% (SF025) and 0.5% fiber (SF050) presented a very similar format, with air inlet suction values and residual suction values virtually equal, to the adjustment methods used.
Reducing Anxiety and Social Stress in Primary Education: A Breath-Focused Heart Rate Variability Biofeedback Intervention

Primary school students suffer from high levels of anxiety and stress. Having emotional regulation abilities can help them to manage challenging emotional situations. Conscious and slow breathing is a physiological, emotional regulation strategy that is feasible for primary school students to learn. Following Polyvagal Theory and PMER Theory, this research presents the results of a breath-focused heart rate variability biofeedback intervention. The intervention aimed to reduce anxiety and physiological and social stress in primary school children. A total of 585 students (46.4% girls and 53.6% boys) from the same public school, aged between 7 and 12 years (M = 8.51; SD = 1.26), participated in this study. To assess the impact of training, a mixed design was used with two groups (Treatment and Control groups), two evaluation phases (Pretest and Post-test), and three educational cycles (first, second and third cycles). To examine heart rate variability, emWave software was used and anxiety and social stress were measured by the BASC II test. The results showed that after the intervention, the students learned to breathe consciously. Moreover, they reduced their levels of anxiety (M(SD)pretest = 12.81(2.22) vs. M(SD)posttest = 13.70(1.98)) and stress (M(SD)pretest = 12.20(1.68) vs. M(SD)posttest = 12.90(1.44)). The work also discusses the limitations and benefits of this type of intervention in primary schools.
Exploiting Game Theoretic Based Coordination Among Appliances in Smart Homes for Efficient Energy Utilization

In this paper, a demand side management (DSM) scheme is used to make energy utilization more efficient. The DSM scheme encourages the consumer to change energy utilization patterns which benefit the utility. In return, the consumer gets some incentives from the utility. The objectives of the proposed DSM system include: electricity bill reduction, reduced peak to average ratio (PAR), and maximization of consumer comfort. In the proposed system, the electrical devices are scheduled by using elephant herding optimization (EHO) and adaptive cuckoo search (ACS) algorithms. Moreover, a new algorithm called hybrid elephant adaptive cuckoo (HEAC) is proposed which uses the features of both former algorithms. A comparison of these algorithms is also presented in terms of three performance parameters. The HEAC shows better performance as compared to EHO and ACS which is evident from the simulation results. Different electricity tariffs are introduced by the utility to provide incentives to the consumers. A regional based time of use (ToU) tariff is used to make the system effective for different types of regions. Moreover, this enables the consumers to act according to the regional environment. The coordination can play a very important role in cost reduction as well as in consumer comfort maximization. The coordination is incorporated among the electrical devices by using cooperative game theory (GT) and dynamic programming (DP). Extensive simulations are performed to show the effectiveness of the proposed scheme in terms of electricity utilization cost, PAR reduction, and consumer comfort maximization.
N-acetyldopamine dimer inhibits neuroinflammation through the TLR4/NF-κB and NLRP3/Caspase-1 pathways

Neuroinflammation mediated by microglia is an important pathophysiological mechanism in neurodegenerative diseases. However, there is a lack of effective drugs to treat neuroinflammation. N-acetyldopamine dimer (NADD) is a natural compound from the traditional Chinese medicine Isaria cicada. In our previous study, we found that NADD can attenuate DSS-induced ulcerative colitis by suppressing the NF-κB and MAPK pathways. Does NADD inhibit neuroinflammation, and what is the target of NADD? To answer this question, lipopolysaccharide (LPS)-stimulated BV-2 microglia was used as a cell model to investigate the effect of NADD on neuroinflammation. Nitric oxide (NO) detection, reactive oxygen species (ROS) detection and enzyme-linked immunosorbent assay (ELISA) results show that NADD attenuates inflammatory signals and proinflammatory cytokines in LPS-stimulated BV-2 microglia, including NO, ROS, tumor necrosis factor (TNF)-α, interleukin (IL)-1β and interleukin-6 (IL-6). Western blot analysis show that NADD inhibits the protein levels of Toll-like receptor 4 (TLR4), nuclear factor kappa-B (NF-κB), NOD-like receptor thermal protein domain associated protein 3 (NLRP3), ASC and cysteinyl aspartate specific proteinase (Caspase)-1, indicating that NADD may inhibit neuroinflammation through the TLR4/NF-κB and NLRP3/Caspase-1 signaling pathways. In addition, surface plasmon resonance assays and molecular docking demonstrate that NADD binds with TLR4 directly. Our study reveals a new role of NADD in inhibiting the TLR4/NF-κB and NLRP3/Caspase-1 pathways, and shows that TLR4-MD2 is the direct target of NADD, which may provide a potential therapeutic candidate for the treatment of neuroinflammation.
The relationship between a ‘polluter pays’ approach to carbon capture, regional policy and ‘just transition’ employment agendas

ABSTRACT Policy makers in a number of nations are currently developing carbon capture and storage (CCS) as an industrial decarbonisation solution, linking capture potential in industry clusters to domestic or overseas offshore storage capacity. However, the design, focus and timeframe for policy support are proving challenging in countries like the UK, where industry actors are concerned about the competitiveness implications of additional operational capital costs, while government aims to offer only transitory policy support. Policy-facing research is required to understand the drivers, nature and extent of potential competitiveness loss from adopting carbon capture in specific industry and country contexts, along with the impacts of policy decisions in other countries and of possible future technology improvements. We consider the case of the UK chemicals industry, using an economy-wide computable general equilibrium (CGE) model. This highlights how macroeconomic and sectoral impacts of concern under regional, industry and climate policy agendas depend on domestic and export demand responses to changing industry prices. A crucial question is whether capture costs are similarly reflected in international prices. We identify a risk of policy commitment to ‘polluter pays’ having sustained negative outcomes for capture firms, along with offshoring/leakage of jobs and GDP, and associated emissions, as demand shifts to lower cost overseas production. However, such costs could be reduced, and some capture industry gains realised, if competitors in other nations ultimately follow in bearing similar costs and particularly if ‘early mover’ action enables firms to make efficiency gains and build comparative advantage in operational carbon capture. Key policy insights A ‘polluter pays’ approach to industrial carbon capture risks triggering potential ‘offshoring’ of manufacturing activity in all timeframes where increased operational costs reduce the relative competitiveness of capture firms. A border tax risks worse industry and wider economy outcomes, where domestic production is intensive in imports of the commodity in question. Transitory policy support should focus on enabling capture firms to build efficiency in using carbon capture equipment while sustaining competitiveness and jobs within regional industry clusters. Opportunities should be explored to develop comparative advantage where policy activity involves ‘early mover’ action on carbon capture.
When did bumblebees reach South America? Unexpectedly old montane species may be explained by Mexican stopover (Hymenoptera: Apidae)

A problem for understanding bumblebee biogeography is that if bumblebees dispersed from Asia through North America to South America, if they are poor at long-distance dispersal with establishment over sea, and if the land bridge between North and South America was not established until c. 3 Ma BP, then there is an apparent conflict with the divergence among currently endemic South American lineages having been dated as early as 15–17 Ma. Using the first complete phylogenetic trees for all known and accepted extant species of the groups involved, we show how this conflict could be resolved. We suggest that characterizing bumblebees as being associated generally with temperate flower-rich meadows conflates divergent habitat specializations between two early lineages, associated with northern lowland grasslands and with southern montane grasslands respectively, which may have driven divergences in behaviour and in biogeographic processes. First, for most of the lowland grassland group of bumblebees, estimated dates of divergence are consistent with dispersal to South America via the land-bridge corridor that opened at c. 3 Ma, followed by extant endemic lineages diverging in situ within South America. In contrast, for the second group that occupies montane grassland habitats (and for a few montane lineages of the ‘lowland’ group), we suggest that dispersal to South America at c. 3 Ma could be consistent with older divergence for currently endemic species if: (1) many of the extant South American lineages had already diverged outside the region before 3 Ma in neighbouring Mesoamerica; and (2) they had been constrained within the high mountains there, dispersing southwards into South America only once the isthmus corridor had become established; and (3) some of those ancestral montane lineages had become extirpated from Mesoamerica during subsequent warm climatic fluctuations. This interpretation re-emphasizes that biogeographic studies need to consider habitat-specific dispersal models that change through time.
Combine Harvester Bearing Fault-Diagnosis Method Based on SDAE-RCmvMSE

In the fault monitoring of rolling bearings, there is always loud noise, leading to poor signal stationariness. How to accurately and efficiently identify the fault type of rolling bearings is a challenge. Based on multivariate multiscale sample entropy (mvMSE), this paper introduces the refined composite mvMSE (RCmvMSE) into the fault extraction of the rolling bearing. A rolling bearing fault-diagnosis method based on stacked auto encoder and RCmvMSE (SDAE-RCmvMSE) is proposed. In the actual environment, the fault-diagnosis method use the multichannel vibration signals of the bearing as the input of stacked denoising autoencoders (SDAEs) to filter the noise of the vibration signals. The features of denoise signals are extracted by RCmvMSE and the rolling bearing operation-state diagnosis is completed with a support-vector machine (SVM) model. The results show that in the original test data, the accuracy rates of SDAE-RCmvMSE, RCmvMSE, and commonplace features of vibration signals combined with SVM (CFVS-SVM) methods are 99.5%, 100%, and 96% respectively. In the data with noise, the accuracy rates of RCmvMSE and CFVS-SVM are 97.75% and 93.08%, respectively, but the accuracy of SDAE-RCmvMSE is still 100%.
Circuit-Parameter-Based Audiosusceptibility Model for Series Resonant Converter

Models that accurately predict the output voltage ripple magnitude are essential for applications with stringent performance target for it. Impact of the dc input ripple on the output ripple for a frequency-controlled series resonant converter (SRC) using a discrete-domain exact discretization modeling method is analyzed in this paper. A novel discrete state-space model along with a small-signal model for the SRC considering three state variables is presented. The audiosusceptibility (AS) transfer function that relates the input-to-output ripple is derived from the small-signal model. Analysis of the AS transfer function indicates a resonance peak and an expression is derived connecting the AS resonance frequency for the input ripple based on the SRC component values. Further analysis is done to show that a set of values for the SRC parameter exists, which forms a design space, for which the normalized gain offered by the SRC for the input ripple is less than unity at any input ripple frequency. A test setup to introduce the variable frequency ripple at the input of the SRC for the experimental evaluation of the AS transfer function is developed. Influence of stray parameters on the AS gain, AS resonance frequency, and on the SRC tank resonance frequency is evaluated. An SRC is designed at a power level of 10 kW. The analysis using the derived analytical model, simulations, and experimental results are found to be closely matching.
The Affect Misattribution in the Interpretation of Ambiguous Stimuli in Terms of Warmth vs. Competence: Behavioral Phenomenon and Its Neural Correlates

Warmth and competence are fundamental dimensions of social cognition. This also applies to the interpretation of ambiguous symbolic stimuli in terms of their relation to warmth or competence. The affective state of an individual may affect the way people interpret the neutral stimuli in the environment. As previous findings have shown, it is possible to alter the perception of neutral social stimuli in terms of warmth vs. competence by eliciting an incidental affect with the use of emotion-laden words. In the current experiment, we expected the valence and origin of an affective state, factors ascribing emotionally laden words, to be able to switch the interpretation of the neutral objects. We have shown in behavioural results that negative valence and reflective origins promote the interpretation of unknown objects in terms of competence rather than warmth. Furthermore, electrophysiological-response-locked analyses revealed differences specific to negative valence while making the decision in the ambiguous task and while executing it. The results of the current experiment show that the usage of warmth and competence in social cognition is susceptible to affective state manipulation. In addition, the results are coherent with the evolutionary perspective on social cognition (valence effects) as well as with predictions of the dual mind model of emotion (origin effects).
Applications of Games to Propositional Proof Complexity

In this thesis we explore a number of ways in which combinatorial games can be used to help prove results in the area of propositional proof complexity. The results in this thesis can be divided into two sets, the first being dedicated to the study of Resolution space (memory) requirements, whereas the second is centered on formalizing the notion of 'dangerous' reductions. The first group of results investigate Resolution space measures by asking questions of the form, 'Given a formula F and integer k, does F have a [Type of Resolution] proof with [Type of Resource] at most k? ' We refer to this as a proof complexity resource problem, and provide comprehensive results for several forms of Resolution as well as various resources. These results include the PSPACE-Completeness of Tree Resolution clause space (and the Prover/Delayer game), the PSPACE-Completeness of Input Resolution derivation total space, and the PSPACE-Hardness of Resolution variable space. This research has theoretical as well as practical motivations: Proof complexity research has focused on the size of proofs, and Resolution space requirements are an interesting new theoretical area of study. In more practical terms, the Resolution proof system forms the underpinnings of all modern SAT-solving algorithms, including clause learning. In practice, the limiting factor on these algorithms is memory space, so there is a strong motivation for better understanding it as a resource. With the second group of results in this thesis we investigate and formalize what it means for a reduction to be 'dangerous'. The area of SAT-solving necessarily employs reductions in order to translate from other domains to SAT, where the power of highly-optimized algorithms can be brought to bear. Researchers have empirically observed that it is unfortunately possible for reductions to map easy instances from the input domain to hard SAT instances. We develop a non-Hamiltonicity proof system and combine it with additional results concerning the Prover/Delayer game from the first part of this thesis as well as proof complexity results for intuitionistic logic in order to provide the first formal examples of harmful and beneficial reductions, ultimately leading to the development of a framework for studying and comparing translations from one language to another.
Predictors of Short-Term Mortality in Patients with Acute Pulmonary Embolism

Background: Pulmonary embolism (PE) is associated with short- and long-term adverse events including mortality. Prompt diagnosis, risk stratification and treatment can improve the outcome. The objective of the present study is to determine the predictors of early death within 30 days in the course of acute pulmonary embolism (APE). Patients and methods: One hundred patients with APE were recruited from both inpatients department and ICUs at Cardiothoracic Minia University Hospital . All patients subjected to detailed history, general and local chest examination. Laboratory investigation included CBC, Hs-CRP, troponin and D-dimer. CT pulmonary angiogram (CTPA) with calculation of pulmonary artery obstructive index (PAOI) using Qandali Score and measurement of right ventricle to left ventricle (RV/LV) ratio, Echo with measurement of pulmonary artery systolic pressure (PASP) were done for all patients. Patients were monitored for 30 days from the onset of symptoms to assess the mortality. Results: Patients classified according to outcome into survivors, 80 (80%) patients and 20 (20%) non-survivors patients. Po2 and Sao2 were significantly higher in survivors (P values 0.0001 and 0.05, respectively). Pulmonary Embolism Severity Index (PESI) was significantly higher in the non-survivor group (P value 0.001). PAOI and RV/LV ratio were higher in non survivors with (P value 0.001 and 0.001, respectively). Also central location of emboli was higher in non survivors representing. PASP was higher in non survivors (P value 0.001). Conclusion: The non-survivor group showed decrease Po2 and Sao2, higher PESI, PAOI, RV/LV ratio, and dilated RV compared with the survivor group. Thus these parameters could be predictors for poor patient outcome.