Object Identification by Signal Gain and Correlation

In this study, “ring rotation invariant transform” techniques are used to add more salient feature to the original images. The “ring rotation invariant transform” can solve image rotation problem, which transfers a ring signal to several signal vectors in the complex domain, whereby to generate invariant magnitude. Matrix correlation is employed to combine these magnitudes to generate the various discriminators, by which to identify objects. For managing image-shifting problem, one pixel in sample image is compared with surrounding pixels of unknown image. The comparison approaching in this study is by the basis of pixel-to-pixel-comparisons.

Critical-like bistable dynamics in the resting-state human brain

Brain activity exhibits scale-free avalanche dynamics and power-law long-range temporal correlations (LRTCs) across the nervous system. This has been thought to reflect "brain criticality", i.e., brains operating near a critical phase transition between disorder and excessive order. Neuronal activity is, however, metabolically costly and may be constrained by activity-limiting mechanisms and resource depletion, which could make the phase transition discontinuous and bistable. Observations of bistability in awake human brain activity have nonetheless remained scarce and its functional significance unclear. First, using computational modelling where bistable synchronization dynamics emerged through local positive feedback, we found bistability to occur exclusively in a regime of critical-like dynamics. We then assessed bistability in vivo with resting-state magnetoencephalography and stereo-encephalography. Bistability was a robust characteristic of cortical oscillations throughout frequency bands from δ (3–7 Hz) to high-γ (100–225 Hz). As predicted by modelling, bistability and LRTCs were positively correlated. Importantly, while moderate levels of bistability were positively correlated with executive functioning, excessive bistability was associated with epileptic pathophysiology and predictive of local epileptogenicity. Critical bistability is thus a salient feature of spontaneous human brain dynamics in awake resting-state and is both functionally and clinically significant. These findings expand the framework of brain criticality and show that critical-like neuronal dynamics in vivo involves both continuous and discontinuous phase transitions in a frequency-, neuroanatomy-, and state-dependent manner.

Impact of industry on agricultural development in Sylhet region of Bangladesh: Farmer’s perception

The study targets at farmer’s perception and their cognition how they conceive that agricultural performance has been affected and devastated through industrial work. It reviews and investigates the opinion of 25% farmers of two villages from each upazila of two named Madhapur and Habiganj sadar upazila in Sylhet division where Charu Ceramic Industry Limited and Olipur industry are located respectively from mid-September to mid-October, 2021 through survey of questionnaire, interview and group discussion. According to 85% farmers, the industry shades agriculture by imposing an adverse and toxic impact on agricultural exposure and development. Among them, (41.6% and 48.4%) of farmers realize that the industry creates high propensity of losing standard quality of soil and water, respectively. They (40.2%) notice that invasion of several dangerous insects on crops has become prominent and unmanageable near the industrial area. The study represents such kind of realization of farmers to show a salient feature in view of their finding causes and intuition with significant numerical data. Int. J. Agril. Res. Innov. Tech. 11(2): 133-138, Dec 2021

Epidemiology study of SARS-CoV-2 pandemic in India, the first and second wave

Background and objectives: SARS-CoV-2 has wrecked the world for the past 17 months. India has been hit by the second wave of the virus which has been characterized by new symptoms. This study focuses on the pattern of infection over the last 13 months utilizing epidemic model to predict course of the pandemic. Material and methods: The data was collected from covid19india.org to perform analysis based on age and gender distribution. Statistical analysis was performed to determine the relation between confirmed and recovered cases while SIR epidemic model was used to determine the course of the pandemic in the country and the changes that have occurred from the first to the second wave. Results and discussions: Results show infectivity rate to be higher in ages 20-50 while mortality is higher in 50-80 age group while 60-70% of the infected population are males. Each of the 9 states have their own salient feature curves of infection. It was seen that the confirmed and recovered cases are more correlated at present than previous wave. The curves for both waves show a polynomial distribution while the reproduction number data shows an almost U-shaped curve indicating decrease of infection spread in the middle phase when the first wave was on a decline before picking up again owing to the second wave. Interpretations and conclusion: The gender and age distribution shows that although lower age group is more infected, mortality is high for higher age groups, on the other hand males are more prone to the infection. The statistical analysis shows the nature of spread of the disease, the data of which is quantified by the SIR model based study.

Desiccation-resurrection linked antioxidant machinery of a moss species Campylopus flexuosus (Hedw.) Bird.

Dehydration and rejuvenation during rehydration is the salient feature of certain plants which can withstand drought. The present study was undertaken to justify the tolerance capacity of Campylopus flexuosus, the moss of the Ponmudi belts of Thiruvananthapuram, against dehydration followed by rehydration. Fresh leafy plants of C. flexuosus were hydrated, afterwards dried, and rehydrated under in vitro environment. In the course of loss of water from cells, the relative water content of desiccated thallus was reduced after 4 h with intense inward curling. Upon rehydration, the RWC was regained 85% of its initial water content within hours. The rehydrated thallus showed the normal morphology. Photosynthetic parameters like chlorophyll b (1.01 to 1.56 μg g –1 ), and total carotenoid (0.251 to 0.514 μg g –1 ) increased remarkably in the desiccated state. Superoxide radical (O2 _) content increased (11.4 nmol/g FW), resulting in an oxidative burst during desiccation. Consequently, antioxidant enzymes such as catalase (0.369 U mg protein −1), superoxide dismutase ( 2.68 to 6.02 Units mg−1), peroxidase ( 0.12 μmol min−1 g−1 protein) and glutathione reductase ( 312 Units mg−1 protein) activities were up-regulated in the desiccated thallus to ameliorate oxidative damage. Increased malondialdehyde (1.08 nmol g−1 FW) content during desiccation substantiates membrane damage and loss of its integrity. During desiccation, the osmolytes sucrose and proline (27.6 and 2.57 μmol/g FW respectively) were enhanced to maintain cell structure integrity. After rehydration, biochemical and morphological properties were maintained similar to hydrated conditions. Thus, the study reflects the unique adaptations of the moss to tide over desiccation tolerance.

Learning Personalized Product Recommendations with Customer Disengagement

Problem definition: We study personalized product recommendations on platforms when customers have unknown preferences. Importantly, customers may disengage when offered poor recommendations. Academic/practical relevance: Online platforms often personalize product recommendations using bandit algorithms, which balance an exploration-exploitation trade-off. However, customer disengagement—a salient feature of platforms in practice—introduces a novel challenge because exploration may cause customers to abandon the platform. We propose a novel algorithm that constrains exploration to improve performance. Methodology: We present evidence of customer disengagement using data from a major airline’s ad campaign; this motivates our model of disengagement, where a customer may abandon the platform when offered irrelevant recommendations. We formulate the customer preference learning problem as a generalized linear bandit, with the notable difference that the customer’s horizon length is a function of past recommendations. Results: We prove that no algorithm can keep all customers engaged. Unfortunately, classical bandit algorithms provably overexplore, causing every customer to eventually disengage. Motivated by the structural properties of the optimal policy in a scalar instance of our problem, we propose modifying bandit learning strategies by constraining the action space up front using an integer program. We prove that this simple modification allows our algorithm to perform well by keeping a significant fraction of customers engaged. Managerial implications: Platforms should be careful to avoid overexploration when learning customer preferences if customers have a high propensity for disengagement. Numerical experiments on movie recommendations data demonstrate that our algorithm can significantly improve customer engagement.

Buddhist Approaches to Impermanence: Phenomenal and Naumenal

The doctrine of impermanence can be called the most salient feature of the Buddha’s teaching. The early Buddhist doctrine of impermanence can be understood in four different but interrelated contexts: Buddha’s empiricism, the notion of conditioned/constituted objects, the idea of dependent arising, and the practical context of suffering and emancipation. While asserting the impermanence of all phenomena, the Buddha was silent on the questions of the so-called transcendent entities and truths. Moreover, though the Buddha described Nibbāṇa/Nirvāṇa as a ‘deathless state’ (‘amataṃ padam’), it does not imply eternality in a metaphysical sense. Whereas the early Buddhist approach to impermanence can be called ‘phenomenal’, the post-Buddhist approach was concerned with naumena (things in themselves). Hence, Sarvāstivāda (along with Pudgalavāda) is marked by absolutism in the form of the doctrines of substantial continuity, atomism, momentariness, and personalism. The paper also deals with the approaches to impermanence of Dharmakīrti and Nāgārjuna, which can be called naumenal rather than strictly phenomenal. For Dharmakīrti, non-eternality was in fact momentariness and it was not a matter of experience but derivable conceptually or analytically from the concept of real. Nāgārjuna stood not for impermanence, but emptiness (śūnyatā), the concept which transcended both impermanence and permanence, substantiality and non-substantiality.

Characterizing Hippocampal Oscillatory Signatures Underlying Seizures in Temporal Lobe Epilepsy

Temporal Lobe Epilepsy (TLE) is a neurological condition characterized by focal brain hyperexcitability, resulting in abnormal neuronal discharge and uncontrollable seizures. The hippocampus, with its inherently highly synchronized firing patterns and relatively high excitability, is prone to epileptic seizures, and it is usually the focus of TLE. Researchers have identified hippocampal high-frequency oscillations (HFOs) as a salient feature in people with TLE and animal models of this disease, arising before or at the onset of the epileptic event. To a certain extent, these pathological HFOs have served as a marker and a potential target for seizure attenuation using electrical or optogenetic interventions. However, many questions remain about whether we can reliably distinguish pathological from non-pathological HFOs and whether they can tell us about the development of the disease. While this would be an arduous task to perform in humans, animal models of TLE provide an excellent opportunity to study the characteristics of HFOs in predicting how epilepsy evolves. This minireview will (1) summarize what we know about the oscillatory disruption in TLE, (2) summarize knowledge about oscillatory changes in the latent period and their role in predicting seizures, and (3) propose future studies essential to uncovering potential treatments based on early detection of pathological HFOs.

Does quantity matter to a stingless bee?

Quantitative information is omnipresent in the world and a wide range of species has been shown to use quantities to optimize their decisions. While most studies have focused on vertebrates, a growing body of research demonstrates that also insects such as honeybees possess basic quantitative abilities that might aid them in finding profitable flower patches. However, it remains unclear if for insects, quantity is a salient feature relative to other stimulus dimensions, or if it is only used as a “last resort” strategy in case other stimulus dimensions are inconclusive. Here, we tested the stingless bee Trigona fuscipennis, a species representative of a vastly understudied group of tropical pollinators, in a quantity discrimination task. In four experiments, we trained wild, free-flying bees on stimuli that depicted either one or four elements. Subsequently, bees were confronted with a choice between stimuli that matched the training stimulus either in terms of quantity or another stimulus dimension. We found that bees were able to discriminate between the two quantities, but performance differed depending on which quantity was rewarded. Furthermore, quantity was more salient than was shape. However, quantity did not measurably influence the bees' decisions when contrasted with color or surface area. Our results demonstrate that just as honeybees, small-brained stingless bees also possess basic quantitative abilities. Moreover, invertebrate pollinators seem to utilize quantity not only as "last resort" but as a salient stimulus dimension. Our study contributes to the growing body of knowledge on quantitative cognition in invertebrate species and adds to our understanding of the evolution of numerical cognition.