Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Degrowth? Making Peace with Mortality to Reconnect with (One's) Nature: An Ecopsychological Proposition for a Paradigm Shift

This article explores the existential conditions for a transition towards socioeconomic degrowth through an analysis of a paradigm shift between two extreme polarities of socio-ecological positioning: the Dominant Social Paradigm (DSP) and the New Ecological Paradigm (NEP). It is suggested that the transition from one to the other – understood as the first collective step towards degrowth – requires a transformation in the way we, in western capitalist society, define ourselves in relation to nature. This identity transformation corresponds with the reconnection between humans and nature that ecopsychology has been calling for since its emergence in the 1970s. However, according to recent empirical studies in existential psychology, such a transformation contains potentially disquieting aspects, since it implies recognising and accepting the idea of our own mortality. Staging a dialogue between ecopsychology and critical degrowth theories, this article argues that the necessary transition towards degrowth requires new ways of dealing with these existential fears – namely, confronting them in a ‘reflexive’ rather than ‘defensive’ way – so as to develop relationships with nature that respect the limits of the biosphere.
RL-Routing: An SDN Routing Algorithm Based on Deep Reinforcement Learning

Communication networks are difficult to model and predict because they have become very sophisticated and dynamic. We develop a reinforcement learning routing algorithm (RL-Routing) to solve a traffic engineering (TE) problem of SDN in terms of throughput and delay. RL-Routing solves the TE problem via experience, instead of building an accurate mathematical model. We consider comprehensive network information for state representation and use one-to-many network configuration for routing choices. Our reward function, which uses network throughput and delay, is adjustable for optimizing either upward or downward network throughput. After appropriate training, the agent learns a policy that predicts future behavior of the underlying network and suggests better routing paths between switches. The simulation results show that RL-Routing obtains higher rewards and enables a host to transfer a large file faster than Open Shortest Path First (OSPF) and Least Loaded (LL) routing algorithms on various network topologies. For example, on the NSFNet topology, the sum of rewards obtained by RL-Routing is 119.30, whereas those of OSPF and LL are 106.59 and 74.76, respectively. The average transmission time for a 40GB file using RL-Routing is <inline-formula><tex-math notation="LaTeX">$\text{25.2}~s$</tex-math></inline-formula>. Those of OSPF and LL are <inline-formula><tex-math notation="LaTeX">$\text{63}~s$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$\text{53.4}~s$</tex-math></inline-formula>, respectively.
Ensemble models for data-poor assessment: accounting for uncertainty in life-history information

Length measurements from fishery catch can be used in data-limited assessments to estimate important population parameters to guide management, but results are highly sensitive to assumptions about biological information. Ideally, local life history studies inform biological parameters. In the absence of reliable local estimates, scientists and managers face the difficult task of agreeing on fixed values for life-history parameters, often leading to additional uncertainty unquantified in the assessment or indecision defaulting to status-quo management. We propose an ensemble approach for incorporating life history uncertainty into data-limited stock assessments. We develop multivariate distributions of growth, mortality, and maturity parameter values, then use bivariate interpolation and stacking as an ensemble learning algorithm to propagate uncertainty into length-based, data-limited stock assessment models. Simulation testing demonstrated that stacking across life history parameter values leads to improved interval coverage over simple model averaging or assuming the parameter distribution means when the true life-history parameter values are unknown. We then applied the stacking approach for a U.S. Caribbean stock where the Scientific and Statistical Committee did not accept the assessment due to uncertainty in life history parameters. Stacking can better characterize uncertainty in stock status whenever life-history parameters are unknown but likely parameter distributions are available.
Neural pattern similarity differentially affects memory performance of younger and older adults: Age differences in neural similarity and memory

Age-related memory decline is associated with changes in neural functioning but little is known about how aging affects the quality of information representation in the brain. Whereas a long-standing hypothesis of the aging literature links cognitive impairments to less distinct neural representations in old age, memory studies have shown that high similarity between activity patterns benefits memory performance for the respective stimuli. Here, we addressed this apparent conflict by investigating between-item representational similarity in 50 younger (19–27 years old) and 63 older (63–75 years old) human adults (male and female) who studied scene-word associations using a mnemonic imagery strategy while electroencephalography was recorded. We compared the similarity of spatiotemporal frequency patterns elicited during encoding of items with different subsequent memory fate. Compared to younger adults, older adults’ memory representations were more similar to each other but items that elicited the most similar activity patterns early in the encoding trial were those that were best remembered by older adults. In contrast, young adults’ memory performance benefited from decreased similarity between earlier and later periods in the encoding trials, which might reflect their better success in forming unique memorable mental images of the joint picture–word pair. Our results advance the understanding of the representational properties that give rise to memory quality as well as how these properties change in the course of aging. Significance statement Declining memory abilities are one of the most evident limitations for humans when growing older. Despite recent advances of our understanding of how the brain represents and stores information in distributed activation patterns, little is known about how the quality of information representation changes during aging and thus affects memory performance. We investigated how the similarity between neural representations relates to subsequent memory quality in younger and older adults. We present novel evidence that the interaction of pattern similarity and memory performance differs between age groups: Older adults benefited from increased similarity during early encoding whereas young adults benefited from decreased similarity between early and later encoding. These results provide insights into the nature of memory and age-related memory deficits.
PHYLOGENETIC ANALYSIS OF ENDEMIC FISH SPECIES OF OHRID LAKE

Computer-assisted analysis in biogeography is becoming one of the major research topics in the physical geography. Interestingly, the bioinformatics software tools provide good models for better understanding of a biological process. We have utilized them in finding the relationship between Ohrid lake endemic species of Salmo Letnica and other eight fishes from the Salmonidae family that constitute three subfamilies. The study of phylogenetics with considerable research interest in the phylogenetic relationships among the endemic fish species of Ohrid Lake is the main focus of this research article. Salmonidae family is found to be a big family constituting three subfamilies including Salmoninae family. The main research of the present work is aimed at the fishes from the Salmoninae family with more focus on the Salmo genus. Eight types of fishes from the mentioned genus were used in the process of creation of two different phylogenetic trees namely Neighbor-Joining and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) phylogenetic tree. In order to create the trees, the accessions codes for the mitochondrial DNA sequences adopted from the National Center for Biotechnology Information website were imported into MATLAB for further analysis. The resulting trees were investigated further to understand clearly the correlation of Salmo Letnica with the other eight fishes.
Development of a deep amplicon sequencing method to determine the proportional species composition of piroplasm haemoprotozoa as an aid in their control

Piroplasmosis is caused by tick-borne haemoprotozoa of the genera Theileria and Babesia. These parasitic infections can cause serious impact on the health of livestock and production. Multiple piroplasm species can infect a single host, but reliable molecular diagnostic tools are needed with which to understand the composition of these complex parasite communities. Theileria and Babesia vary in their epidemiology, drug sensitivity, pathogenicity and interaction of co-infecting species, but are similar in the animals, become persistent carriers after recovery from primary infection, acting as reservoir hosts. Here, we describe for the first time the use of a deep amplicon sequencing platform to identify proportions of piroplasm species in co-infecting communities and develop the concept of a “haemoprotobiome”. First, four phenotypically-verified species of Theileria and Babesia were used to prepare mock pools with random amounts of the parasites and amplified with four different numbers of PCR cycles to assess sequence representation of each species. Second, we evaluated the detection threshold of the deep amplicon sequencing assay for each of the four species and to assess the accuracy of proportional quantification of all four species. Finally, we applied the assay to the field samples to afford insight of the species composition of piroplasm communities in small and large ruminants in the Punjab province of Pakistan. The “haemoprotobiome” concept has several potential applications in veterinary and human research, including understanding of responses to drug treatment; parasite epidemiology and ecology; species interactions during mixed infections; and parasite control strategies.
Five evidences on labour productivity and inequality association in Italy

In the past two decades, Italy experienced a deceleration in labour productivity growth accompanied by persistently high income inequality. In this paper, we analyze five main empirical evidences for Italy indicating possible common determinants and linkages between productivity growth and income inequality in the period 1995-2018. To the best of our knowledge, the literature investigating this relationship for Italy is still very scarce. According to our preliminary exploration, the association between Italian productivity growth and income inequality between 1995 and 2018 has been mostly negative. This evidence suggests that the gloomy dynamics of productivity might have been an obstacle to income inequality reduction. There is also the possibility, however, that income inequality itself was among the causes of the gloomy productivity growth.
Detection of Thoracic Diseases using Deep Learning

The study of using deep learning for detection of various thoracic diseases has been an active and challenging research area. Chest X-rays are currently the most common and globally used radiology practices for detecting thoracic diseases. Patients suffering from thoracic diseases need to take Chest X-Rays which are read by radiologists and a report is generated by them. However, today with the increase in the number of thoracic patients, a quick method to classify the disease and generate the report has become necessary. Also, patient history has to be considered for diagnosis. This paper offers a comparative study on the various deep learning techniques that can process chest x-rays and are capable of detecting the different thoracic diseases. Also, a technique has been proposed to classify 14 diseases namely Atelectasis, Cardiomegaly, Consolidation, Edema, Effusion, Emphysema, Fibrosis, Hernia, Infiltration, Mass, Nodule, Pneumonia, Pneumothorax, Pleural thickening based on the given X-rays using Residual Neural Network.
High-Resolution Angle-of-Arrival and Channel Estimation for mmWave Massive MIMO Systems With Lens Antenna Array

Lens antenna array (LAA), as a promising architecture in millimeter-wave (mmWave) massive MIMO systems, which can considerably reduce the number of required radio-frequency (RF) chains. In this article, we propose a high-resolution channel or angle-of-arrival (AoA) estimation scheme while taking into account the power leakage problem. Specifically, the criterion function is constructed based on DFT beam difference (DBD) to infer the real position of arrived signal. Subsequently, the novel antenna selection and path number estimation algorithms are proposed without prior knowledge of channel. A few groups of antennas are selected to connect to the RF chains, where each group contains only a small number of antennas. Thus, the beamspace multiple signal classification (MUSIC) algorithm can be implemented in low dimensional space to estimate the AoA(s) for each group. Then the channel estimation can be obtained by least square method after the reconstructions of steering vectors using the AoA estimations. Furthermore, the corresponding spatial smoothing algorithm is leveraged to tackle rank deficient problem at the scenario of constant path gains. Simulation results verify the effectiveness of the proposed scheme.
Possible action of grape seed oil on brain toxicity induced by methomyl or imidacloprid of male rats.

The present study was planned to investigate the effect of methomyl or imidacloprid on the brain of male rats. The effect grape seeds oil as an antioxidant was also evaluated. Animals were administered orally with 1/10 and 1/20 of LD50 methomyl and imidacloprid with 17 and 450 mg /kg bw for four and eight weeks. Grape seeds oil with 4 ml/kg b.wt. was used for protection from methomyl and imidacloprid toxicity. Brain cortex and hippocampus oxidative stress (glutathione S transferase GST, glutathione peroxidase GPX, superoxide dismutase SOD, malondialdhyde MDA and nitric oxide NO), Na+,K+, ATPase and acetyl-cholinesterase AChE were determined. The result showed that GST, GPX, MDA, and NO2 were increased significantly. But SOD, Na+K+ATPase and AChE were significantly reduced in comparison with the control. Grape seed oil induced a significant improvement for the pesticides brain toxicity but not to the level of control. The study suggested that the oil antioxidants not improve the brain toxicity induced by methomyl or imidacloprid.
Awareness or Persuasion? How Free Sampling Affects Crowdfunding Performance

Free sampling, which has been widely applied and studied in marketing, has recently been adopted by entrepreneurs on crowdfunding platforms. Using a dataset from a unique crowdfunding platform, we study whether opting to provide free samples to potential backers increases the likelihood of a campaign meeting its goal. We also investigate how free sampling influences the fundraising dynamics. Using a matched sample of crowdfunding campaigns, we demonstrate that providing free samples significantly improves crowdfunding performance. And among those projects which opt for free sampling, persuasion effect during the report period contributes to the positive effect. The higher the score from the evaluator, the more successful the campaign will be. We also find that the longer the investors are exposed to the evaluation report, the more money is raised.
Suggestions for second-pass anti-COVID-19 drugs based on the Artificial Intelligence measures of molecular similarity, shape and pharmacophore distribution.

Artificial Intelligence algorithms are used to identify “progeny” drugs that are similar to the “parents” already being tested against COVID-19. These algorithms assess similarity not only by the molecular make-up of the molecules, but also by the “context” in which specific functional groups are arrangedand/or by three-dimensional distribution of pharmacophores. The parent-progeny relationships span same-indication drugs (mostly antivirals) as well as those in which the “progenies” have different and perhaps less intuitive primary indications (e.g., immunosuppressant or anti-cancer progenies from antiviral parents). The “progenies” are either already approved drugs or medications in advanced clinical trials – should the currently tested “parent” medicines fail in clinical trials, these “progenies” could be, therefore, re-purposed against the COVID-19 on the timescales relevant to the current pandemic.
Joint CFO and Channel Estimation in OFDM Systems Using Sparse Bayesian Learning

In this article, we study the problem of joint carrier frequency offset (CFO) and sparse channel estimation in orthogonal frequency-division multiplexing (OFDM) communication systems, from the perspective of sparse Bayesian learning (SBL) framework. We first consider the problem in the compressed sensing (CS) context and reformulate it as the problem of recovering a sparse vector from the received signal when CFO and noise variance are unknown parameters that should also be estimated. A novel SBL-based scheme has then been designed to iteratively estimate the CFO, channel impulse response (CIR), and variance of the noise jointly, using the expectation-maximization (EM) algorithm. Both theoretical analysis and simulation results confirm that the proposed scheme outperforms the existing methods while requiring a lower computational cost.
Studies on antioxidant potential, phytochemical properties and toxicity of four popular medicinal plants of Bangladesh

Medicinal plant extract has long been used successfully in ‘unani’ or ‘ayurvedic’ medicine. Medicinal plant extract contains bioactive molecules and activity of these molecules may help to mitigate, eradicate or cure diseases. In the advent for the search for new medicinally important bioactive molecule, the current paper deals with the anti-oxidative, cytotoxic and phytochemical analysis of Scoparia dulcis leaf and root, Curculigo orchioides root, Pandanus fascicularis root and Baccaurea sapida leaf extract. Aqueous and methanolic extracts were made for each of the extracts where they posses significant antioxidative properties. High activities were seen in P. fascicularis and S. dulcis plant extract where IC50 values were 21.87 μg/ml and 173.36 μg/ml respectively. In toxicity test, only P. fascicularis extracts showed lethality in a dose-dependent manner where the LD50 value was 25.64 μg/ml. By the phytochemical analysis, it was found that each of these plant species possesses glycosides, protein, carbohydrates, alkaloid, flavonoid etc. which are pharmacologically active biomolecules. These important properties of those plants showed an indication that these plants can further be tested for the utilization in therapeutic purpose or in cosmetic industry.J. bio-sci. 25: 27-37, 2017
Ocean warming drives decline in coral metabolism while acidification highlights species-specific responses

ABSTRACT Ocean warming and acidification can have negative implications on coral reefs. This mechanistic study aims to evaluate the proximal causes of the observed negative response of Hawaiian corals to climate change scenarios. Net calcification (Gnet), gross photosynthesis, and dark respiration were measured in three species of Hawaiian corals across a range of temperature and acidification regimes using endpoint incubations. Calcification rates showed a curvilinear response with temperature, with the highest calcification rates observed at 26°C. Coral response to ocean acidification (OA) was species dependent and highly variable. OA enhanced calcification rates by 45% in the perforate coral, Montipora capitata, but had no short-term effect on the calcification or photosynthetic rates of imperforate corals, Pocillopora damicornis or Leptastrea purpurea. Further investigations revealed M. capitata to effectively dissipate protons (H+) while increasing uptake of bicarbonate (), therefore maintaining high rates of Gnet under acute OA stress. This study demonstrates the first experimental evidence of the ability of a coral species to take advantage of increased dissolved inorganic carbon and overcome an increasing proton gradient in the boundary layer under OA conditions. These observed differences in coral metabolism may underlie the species-specific responses to climate change.
Foraging preferences of ants on a heterogeneous Brazilian sandy shore habitat

1. Ants may select their food in response to nutritional needs of the colony and forage in a way that optimises a complementary nutrition. Even though resource availability is known to affect ant colony and individual health, there is still no study that has investigated the plastic preferences of ants according to spatial resource availability in naturally heterogeneous conditions.
Robotic batting and motion estimation of objects in free flight

This thesis addresses the problem of a robotic arm striking an object in free flight to a target, and a closely related problem of estimating its pose and motion during the flight based on vision. Both problems share a common theme of dealing with a free flying object that is often not considered in robotics applications. Our investigation draws upon techniques from robotic manipulation, planning, mechanics, state estimation, aerodynamics, and camera modeling. The robot batting problem is a skillful task that requires accurate perception of the flying object, robust modeling of impact dynamics, and efficient planning of a robotic arm’s motion. Leveraging of impact and measuring motion are of great importance in manufacturing, sports, and space robots. To demonstrate the use of impact, we solve the batting problem in two dimensions based on impulse and energetic restitution with friction, flight mechanics incorporating gravity and aerodynamic forces, and trajectory re-planning for the bat-wielding robotic arm. Experiments with different objects show better batting performance than a human with no training. The component of estimating the pose and motion of an in-flight object is subsequently extended to three dimensions. We present a stereo vision system consisting of two high-speed cameras. A hypothesisbased algorithm is proposed to track the object’s features across a sequence of images, and for each active hypothesis, Kalman filtering is employed to compete for the estimation of linear and angular motions. A constrained Kalman filter is introduced to handle multiple quadratic constraints from the estimation of quaternions. Aerodynamic forces for a general shape are modeled through computational fluid dynamics, and the constraint of two-view geometry from stereo cameras is considered in measurements from images. Results have been obtained from the flights of two objects, and compared against calculations based on accelerometer data and image coordinates.
Millimeter-Wave Ultrawideband Circularly Polarized Planar Array Antenna Using Bold-C Spiral Elements With Concept of Tightly Coupled Array

An ultrawideband circularly polarized (CP) planar array antenna built by new radiation elements, the bold-C spiral elements, in millimeter-wave band is presented in this article. Using the tightly coupled array (TCA) technique, the embedded CP bold-C spiral element in the infinite array has achieved both impedance bandwidth and 3 dB axial ratio (AR) bandwidth of 50.7% covering 18.1–30.4 GHz for the fixed broadside beam. Then, a feeding network is designed by using the dielectric-based inverted microstrip gap waveguide (DIMGW) technology in order to have a compact layout. An $8\times 8$ CP planar array based on the proposed radiating element and the feeding network is designed and prototyped. The measured results show that the impedance bandwidth of the whole array for the reflection coefficient below −10 dB is 49% from 18.2 to 30 GHz, and 3 dB AR bandwidth is 44.9% covering 19–30 GHz.