Neurofeedback (NF) shows promise in enhancing memory, but its application to the medial temporal lobe (MTL) still needs to be studied. Therefore, we aimed to develop an NF system for the memory function of the MTL and examine neural activity changes, and memory task score changes through NF training. We created a memory NF system using intracranial electrodes to acquire and visualise the neural activity of the MTL during memory encoding. Twenty trials of a tug-of-war game per session were employed for NF and designed to control neural activity bidirectionally (Up/Down condition). NF training was conducted with three patients with intractable epilepsy, and we observed an increasing difference in NF signal between conditions (Up−Down) as NF training progressed. Similarities and negative correlation tendencies between the transition of neural activity and the transition of memory function were also observed. Our findings demonstrate NF's potential to modulate MTL activity and memory encoding. Future research needs further improvements to the NF system to validate its effects on memory functions. Nonetheless, this study represents a crucial step in understanding NF's application to memory and provides valuable insights for developing more efficient memory enhancement strategies.

Kynurenic acid (KYNA) is an endogenous tryptophan (Trp) metabolite known to possess neuroprotective property. KYNA plays critical roles in nociception, neurodegeneration, and neuroinflammation. A lower level of KYNA is observed in patients with neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases or psychiatric disorders such as depression and autism spectrum disorders, whereas a higher level of KYNA is associated with the pathogenesis of schizophrenia. Little is known about the optimal concentration for neuroprotection and the threshold for neurotoxicity. In this study the effects of KYNA on memory functions were investigated by passive avoidance test in mice. Six different doses of KYNA were administered intracerebroventricularly to previously trained CFLP mice and they were observed following 24 hours. High doses of KYNA (i.e., 20-40 μg/2 μl) significantly decreased the avoidance latency, whereas a low dose of KYNA (0.5 μg/2 μl) significantly elevated it compared with controls, suggesting that the low dose of KYNA enhanced memory function. Furthermore, six different receptor blockers were applied to reveal the mechanisms underlying the memory enhancement induced by KYNA. The series of tests revealed the possible involvement of the serotonergic, dopaminergic, α and β adrenergic, and opiate systems in the nootropic effect. The study confirmed that a low dose of KYNA improved a memory component of cognitive domain, which was mediated by, at least in part, four systems of neurotransmission in an animal model of learning and memory.

The present study examined mechanisms underlying memory deficits in patients with Parkinson disease (PD)and their associations with structural metrics. Nineteen PD and 22 matched controls underwent two memory experiments. In experiment 1 (delayed memory task), subjects were asked to remember an array of colored rectangles with varying memory set sizes [Low-Load (2 items), Low-Load with Distractor, & High-Load (5 items)]. After a 7s delay period, they reported whether the orientation of any relevant figures had changed (test period). In experiment 2 (working memory task), memory arrays were presented in varying set sizes (2 to 6 items) with no distractors that were followed by a 2s delay period and subsequent test period. Brain MRI data were acquired to assess structural differences (volumes and cortical thickness) in brain areas related to attention, working memory storage, and episodic memory. Compared to controls, PD patients had lower memory capacity scores in all memory load conditions for experiment 1 (p <0.021) whereas there were no group differences in any memory load conditions for experiment 2 (p>0.06). In addition, PD patients had lower thickness in the left superior temporal gyrus (p=0.02). Lower thickness values in the left superior temporal gyrus were significant predictors of lower delayed memory performance in Low-Load and Low-Load with Distractor conditions (ps’<0.044) and working memory performance of memory load conditions of 4 and 5 items (p’s<0.012). The present findings suggest that PD patients may have intact working memory storage capacity but impaired attentional filtering and memory consolidation that may lead to lower delayed memory scores. Lower delayed memory in PD may partly be associated with lower cortical thickness in the left superior temporal gyrus.

Memory is probably one of the most complex cognitive functions of the human, and in many years, thousands of studies have helped us to better recognize this brain function. One of the reference textbooks in neuroscience, which has also elaborated on the memory function, is written by Prof. Kandel and his colleagues. In this book, I encountered a number of ambiguities when it was explaining the memory system. Here, I am sharing those points, either to find an answer for them, or to let them be a suggestion for our future works. Prof. Kandel has spent most of his meritorious lifetime on studying the memory system; however, the brain is extremely complex, and as a result, we still have many years to comprehensively understand the neural mechanisms of brain functions.

We discuss a topological method of storing and retrieving information from flash memory. We first present a sensing method where the threshold voltage level, as represented by a sensing time, is extracted in one sensing cycle. The sense time distribution from one set of flash cells, e.g. one physical row, is then processed in software to decode the digital state of each cell. The decoding method uses topological constraints but no rigid or predetermined voltage thresholds to digitize the distribution. The software defined nature of the topologically defined flash (TDF) allows greater flexibility for allocating cells to arbitrary number of digital states.

Counterfeiting electronic components is a serious problem for the security and reliability of any electronic systems. Unfortunately, the number of counterfeit components has increased considerably after the introduction of horizontal semiconductor supply chain. In this paper, we propose a new method for detecting recycled Flash memory, a major target of the counterfeiters due to its ubiquitous usage. Proposed method is based on measurement of change in Flash array characteristics (such as erase time, program time, fail bit count, etc.) with its usage. We find that erase time is the best metric to distinguish a used Flash chip from a fresh one for the following reasons: (1) erase time shows minimal variation among different fresh memory blocks/chip and (2) erase time increases significantly with usage. We verify our method for a wide range of commercial off the shelf Flash chips from several vendors, technology nodes, storage density and storage type (single-bit per cell and multi-bit per cell). The minimum detectable chip usage varies from 0.05% to 3.0% of its total lifetime depending on the exact details of the chip.

Loss of function of the hippocampus or frontal cortex is associated with reduced performance on memory tasks in which subjects are incidentally exposed to cues at specific places in the environment and are subsequently asked to recollect the location at which the cue was experienced. Here, we examined the roles of the rodent hippocampus and frontal cortex in cue-directed attention during encoding of memory for the location of a single incidentally experienced cue. During a spatial sensory preconditioning task, rats explored an elevated platform while an auditory cue was incidentally presented at one corner. The opposite corner acted as an unpaired control location. The rats demonstrated recollection of location by avoiding the paired corner after the auditory cue was in turn paired with shock. Damage to either the dorsal hippocampus or the frontal cortex impaired this memory ability. However, we also found that hippocampal lesions enhanced attention directed towards the cue during the encoding phase while frontal cortical lesions reduced cue-directed attention. These results suggest that the deficit in spatial sensory preconditioning caused by frontal cortical damage may be mediated by inattention to the location of cues during the latent encoding phase, while deficits following hippocampal damage must be related to other mechanisms such as generation of neural plasticity.

We investigated the role of the human medio-temporal complex (hMT+) in the memory encoding and storage of a sequence of four coherently moving RDKs by applying repetitive transcranial magnetic stimulation (rTMS) during an early or late phase of the retention interval. Moreover, in a second experiment we also tested whether disrupting the functional integrity of hMT+ during the early phase impaired the precision of the encoded motion directions. Overall, results showed that both recognition accuracy and precision were worse in middle serial positions, suggesting the occurrence of primacy and recency effects. We found that rTMS delivered during the early (but not the late) phase of the retention interval was able to impair not only recognition of RDKs, but also the precision of the retained motion direction. However, such impairment occurred only for RDKs presented in middle positions along the presented sequence, where performance was already closer to chance level. Altogether these findings suggest an involvement of hMT+ in the memory encoding of visual motion direction. Given that both position sequence and rTMS modulated not only recognition but also precision of the stored information, these findings are in support of a model of visual short-term memory with a variable resolution of each stored item, consistent with the assigned amount of memory resources, and that such item-specific memory resolution is supported by the functional integrity of area hMT+.

This paper describes an $\sim {\cal O}(n)$ pre-compute technique to speed up the Karatsuba algorithm for multiplying two numbers.

A statistical analysis of semantic memory should reflect the complex, multifactorial structure of the relations among its items. Still, a dominant paradigm in the study of semantic memory has been the idea that the mental representation of concepts is structured along a simple branching tree spanned by superordinate and subordinate categories. We propose a generative model of item representation with correlations that overcomes the limitations of a tree structure. The items are generated through "factors" that represent semantic features or real-world attributes. The correlation between items has its source in the extent to which items share such factors and the strength of such factors: if many factors are balanced, correlations are overall low; whereas if a few factors dominate, they become strong. Our model allows for correlations that are neither trivial nor hierarchical, but may reproduce the general spectrum of correlations present in a data-set of nouns. We provide an estimate of the number of concepts that can be stored and retrieved by a large-scale cortical network, the Potts network, which is perhaps approximately 10⁷ with human cortical parameters. When this storage capacity is exceeded, however, retrieval fails completely only for balanced factors; above a critical degree of imbalance, a phase transition leads to a regime where the network still extracts considerable information about the cued item, even if not recovering its detailed representation: partial categorization seems to emerge spontaneously as a consequence of the dominance of particular factors, rather than being imposed ad hoc. We argue this to be a relevant model of semantic memory resilience in Tulving’s remember/know paradigms.

Dementia is a public health priority, in which memory impairments are prevalent and affects an individual’s daily activities. Research has tried to find ways to support memory problems of individuals with dementia. Self reference effect (SRE) has been shown to benefit memory in healthy, non-dementia group. The study aimed to investigate if SRE will improve memory performance of individuals with dementia. We used ecologically valid Ownership Procedure and the Remember/Know Paradigm to examine the Self-Reference Effect (SRE) on memory. It was hypothesised that participants living with dementia will perform differently in the recall of items that were self-referentially encoded compared to items other-referentially encoded and that the memory will be different in control participants than in those that live with dementia. The research found that self-referential processes did not have effect on memory in individuals with dementia. We suggest that impaired self-awareness may have contributed to the lack of this effect. However, we had a small sample size and these findings should be treated with caution.

To live in the information society means to be surrounded by billions of electronic devices full of sensors that constantly acquire data. This enormous amount of data must be processed and classified. A solution commonly adopted is to send these data to server farms to be remotely elaborated. The drawback is a huge battery drain due to high amount of information that must be exchanged. To compensate this problem data must be processed locally, near the sensor itself. But this solution requires huge computational capabilities. While microprocessors, even mobile ones, nowadays have enough computational power, their performance are severely limited by the Memory Wall problem. Memories are too slow, so microprocessors cannot fetch enough data from them, greatly limiting their performance. A solution is the Processing-In-Memory (PIM) approach. New memories are designed that are able to elaborate data inside them eliminating the Memory Wall problem. In this work we present an example of such system, using as a case of study the Bitmap Indexing algorithm. Such algorithm is used to classify data coming from many sources in parallel. We propose an hardware accelerator designed around the Processing-In-Memory approach, that is capable of implementing this algorithm and that can also be reconfigured to do other tasks or to work as standard memory. The architecture has been synthesized using CMOS technology. The results that we have obtained highlights that, not only it is possible to process and classify huge amount of data locally, but also that it is possible to obtain this result with a very low power consumption.

Corresponding to the principles of biological synapses, an essential prerequisite for hardware neural networks using electronics devices is continuous regulation of conductance. We implemented artificial synaptic characteristics in a (GeTe/Sb2Te3)16 iPCM with a superlattice structure under optimized identical pulse trains. Based on atomically controlling the Ge switch in the phase transition that appears in the GeTe/Sb2Te3 superlattice structure, multiple conductance states were implemented by applying the appropriate electrical pulses. Furthermore, we found that the bidirectional switching behavior of a (GeTe/Sb2Te3)16 iPCM can achieve a desired resistance level using the pulse width. Therefore, we also fabricated a Ge2Sb2Te5 PCM and designed a pulse scheme based on the phase transition mechanism to compare to the (GeTe/Sb2Te3)16 iPCM. We designed an identical pulse scheme that implements linear and symmetrical LTP and LTD based on the iPCM mechanism. As a result, the (GeTe/Sb2Te3)16 iPCM showed relatively excellent synaptic characteristics by implementing gradual conductance modulation, a nonlinearity value of 0.32, and LTP/LTD 40 conductance states using identical pulses trains. Our results demonstrate the general applicability of the artificial synaptic device for potential use in neuro-inspired computing and next generation non-volatile memory.

One-dimensional shape memory polymer fibers (SMPFs) have obvious advantages in mechanical properties, dispersion properties and weavability. In this work, a method for fabricating semi-crystallization ethylene-vinyl acetate copolymer (EVA) fiber with two-way shape memory effect by melt spinning and ultraviolet (UV) curing was developed. Here, the effect of crosslink density on its performance was systematically analyzed by gel fraction measurement, tensile tests, DSC and TMA analysis. The results showed that the crosslink density and shape memory properties of EVA fiber could be facilely adjusted by controlling UV curing time. The resulting EVA fiber with cylindrical structure had a diameter of 247.13 ± 10.07 μm, and its mechanical strength and elongation at break were 64.46 MPa and 114.33%, respectively. The critical impact of the crosslink density and applied constant stress on the two-way shape memory effect were analyzed. Moreover, the single EVA fiber could lift more than 143 times its own weight and achieve 9% reversible actuation strain. The reversible actuation capability was significantly enhanced by a simple winding design of the single EVA fiber, which provided great potential applications in smart textiles, flexible actuators and artificial muscles.

Understanding the complex relationship between sleep and memory is a major challenge in neuroscience. Many studies on memory consolidation in humans suggest that sleep triggers offline memory processes, resulting in less forgetting of declarative memory and performance stabilization in non-declarative memory. However, issues related to non-optimal experimental designs, task characteristics and measurements, and inappropriate data analysis practices can significantly affect the interpretation of the effect of sleep on memory. In this article, we discuss these issues and suggest constructive solutions to address them. We believe that implementing these solutions in future sleep and memory research will significantly advance this field by improving the understanding of the specific role of sleep in memory consolidation.

Norepinephrine plays an important role in modulating memory consolidation and evocation through its beta-adrenergic receptors (Adrβ: β1, β2 and β3), which are expressed in the hippocampus (HC) and amygdala (AMY). Here we hypothesized that multisensory stimulation would reverse the memory impairment caused by the inactivation of the Adrβ3 with consequent inhibition of sustained glial-mediated inflammation and glutamatergic depuration. To test this, 21- and 86-day-old Adrβ3KO mice and respective controls underwent to (i) gustative and olfactive stimuli of positive and negative valence associated with (ii) intellectual challenges to reach the food in addition to (iii) objects in hidden places (iv) foraging for 8 weeks followed by (v) analysis of GFAP, Iba-1 and EAAT2 protein expression in the HC and AMY. While this protocol restored the memory impairment when applied to Adrβ3KO animals immediately after weaning, it had no effect when applied to adult animals. In fact, we observed that aging worsens the memory of Adrβ3KO mice. Although no significant expression of GFAP and Iba1 were observed in HC of young and old mice, Adrβ3KO increased EAAT2 expression HC of old mice, while MS didn’t change EAAT2 in young mice but enhanced it expression in older. Relative to AMY of old mice Adrβ3KO increased GFAP expression compared whit WT mice and MS sustained the GFAP expression and increased the EAAT2 expression compared with WT group. These results suggest that a richer and more diverse environment helps to correct memory impairment when applied right after weaning Adrβ3KO animals, also show that the changes in GFAP, Iba1 and EAAT2 expression levels in young and old mice indicate a functional significance in the process of learning and memory and that the control of neuroinflammation in limbic areas mediates this response. They also reinforce the idea that disruption of noradrenergic signaling could be involved in the cognitive impairment observed later in life.

This paper reports a rational design of temperature-responsive nanofiber meshes with shape-memory effect. The meshes were fabricated by electrospinning a poly(ε-caprolactone) (PCL)-based polyurethane with different contents of soft and hard segments. The effects of PCL diol/hexamethylene diisocyanate (HDI)/1,4-butanediol (BD) molar ratio in terms of the contents of soft and hard segments on the shape-memory properties were investigated. Although the mechanical property improved with increasing hard segment ratio, optimal shape-memory properties were obtained with a PCL/HDI/BD molar ratio of 1:4:3. At a microscopic level, the original nanofibrous structure was easily deformed into a temporary shape, and recovered its original structure when the sample was reheated. A higher recovery rate (>89%) was achieved even when the mesh was deformed up to 400%. Finally, the nanofiber meshes were used to control the alignment of human mesenchymal stem cells (hMSCs). The hMSCs aligned well along the fiber orientation. The proposed nanofibrous meshes with the shape-memory effect have the potential to serve as in vitro platforms for the investigation of cell functions as well as implantable scaffolds for wound-healing applications.

Brain physiology and morphology are vulnerable to chronic stress, affecting cognitive performance and behavior. However, functional compounds found in food may alleviate these alterations. White quinoa (Chenopodium quinoa, Wild) seeds have high content of n-3 fatty acids, including alpha-linolenic acid. This work aimed to evaluate the possible neuroprotective role of a quinoa-based functional food (QFF) in rats. Prepubertal male Sprague-Dawley rats were fed with rat chow or QFF (50% rat chow + 50% dehydrated quinoa seeds) and exposed or not to restraint stress protocol (2 hours/day; 15 days). Four experimental groups were used: Non-stressed (rat chow), Non-stressed + QFF, Stressed (rat chow) and Stressed + QFF. Weight gain, locomotor activity (open field), anxiety (elevated plus maze, light-dark box), spatial memory (Y-maze), and dendritic length in the hippocampus were measured in all animals. QFF intake did not affect anxiety-like behaviors, while the memory of stressed rats fed with QFF improved compared to those fed with rat chow. In addition, QFF intake countered the stress-induced dendritic atrophy in pyramidal neurons located in CA3 area of the hippocampus. The results suggest that a quinoa-supplemented diet could have a protective role on the memory of chronically stressed rats.

Trauma in childhood and adolescence has long-term negative consequences in brain development and behavior and increases the risk for psychiatric disorders. Among them, post-traumatic stress disorder (PTSD) during adolescence illustrates the connection between trauma and substance misuse, as adolescents may utilize substances to cope with PTSD. Drug misuse may in turn lead to neuroadaptations in learning processes that facilitate the consolidation of traumatic memories that perpetuate PTSD. This reflects, apart from common genetic and epigenetic modifications, overlapping neurocircuitry engagement triggered by stress and drug misuse that includes structural and functional changes in limbic brain regions and the salience, default-mode, and frontoparietal networks. Effective strategies to prevent PTSD are needed to limit the negative consequences associated with the later development of a substance use disorder (SUD). In this review, we will examine the link between PTSD and SUDs, along with the resulting effects on memory, focusing on the connection between the development of a SUD in individuals who struggled with PTSD in adolescence. Neuroimaging has emerged as a powerful tool to provide insight into the brain mechanisms underlying the connection of PTSD in adolescence and the development of SUDs.

The current theories of consciousness do not address the two major problems:What is the solution to the hard problem of consciousness or What is the experience of self-existence? and How is conscious perception computed? We address these questions using our hypothesized theory:The Self Simulation theory and propose a model of computation of consciousness.The components of the model are an interconnected network of auxiliary processors or Auxiliary Neural Networks(AN) which receives input from the external sensory modalities,computes a representation of the information and relays it to the NCC(Neural Correlates of Consciousness), the NCC – a processing unit which can be neuro anatomically distributed in location but computationally connected to each other and to the Auxiliary Networks,and a working memory which the NCC references for further computation of information.Computation of conscious perception is achieved via the decoding of the content of the memory by the NCC.The self simulation theory accounts not only for the various phenomenal experiences but also experimentation paradigms conducted in the past.

Neutrophils as innate immune cells primarily act as first responders in acute infection and directly maintain inflammatory responses. However, a growing body of evidence suggests that neutrophils also bear the potential to mediate chronic inflammation by exhibiting memory-like features. We recently showed that priming by serial doses of lipopolysaccharide (LPS) from gram-negative bacteria can trigger opposing memory-like responses (exaggerated inflammation, i.e. trained sensitivity or suppression of inflammation, i.e. tolerance) depending on the LPS-dose. We now asked whether this observation could also hold true for lipoteichoic acid (LTA) from gram-positive S. aureus. We found comparable effects of LTA on neutrophil priming as seen for LPS. Low-dose (1 ng/mL) LTA-priming promoted increased production of pro-inflammatory mediators (i.e., TNF-α, IL-6, ROS), whereas high-dose (10 µg/mL) results in contrary reactions supporting anti-inflammatory responses by increased IL-10 and declined pro-inflammatory capacity. In vitro neutrophil recruitment was similarly regulated by LTA -priming. Investigation of signalling patterns revealed TLR2/MyD88-mediated regulation of NFκB-p65 through intermediate PI3Ks/MAPK. Collectively, our data suggest a previously unknown capacity of neutrophils to be differentially primed by varying doses of LTA, endorsing memory-like features in neutrophils.

Re-creation of the past of historical buildings sits at the intersection of the spatio-temporal manifestation of cultural memories, socio-cultural meanings, values and identity re-moulds and refines the existing understanding and sense of place. Digital technologies have become a popular tool in re-creation of the past by creating a new body of knowledge and historical discourse based on identifying the gaps within our written histories. Designers and policymakers around the world have been exploring various tools and technologies such as diachronic modelling yet there is a gap in evidence-based understanding regarding the actual functioning and success of application for place making. This paper, therefore, sets out to scrutinise the role of digital technologies in facilitating digital place making. To do so, it investigates the potential of a new “digital heritage” narrative in the revival of the lost architectural narrative of the Dennys Lascelles Wool Store, Geelong. The proposed paper aims to investigate the potential of a new “digital heritage” narrative and story-telling as a means towards digital place making framework. While exploring the new and unique capabilities provided by the digital narrative in capturing, simulating and disseminating ‘lost’ heritage it will further imbue a sense of place by connecting the everyday city dweller.

In recent years, many molecular and environmental factors have been studied to understand how synaptic plasticity is modulated. Sleep, as an evolutionary conserved biological function, has shown to be a critical player for the consolidation and filtering of synaptic circuitry underlying memory traces. Although sleep disturbances do not alter normal memory consolidation, they may reflect fundamental circuit malfunctions that can play a significant role in exacerbating diseases, such as autism and Alzheimer’s disease. Very recently, scientists sought to answer part of this enigma and they identified p75 neurotrophic receptor (p75NTR) as a critical player in mediating impairments in hippocampal-dependent associative plasticity upon sleep deprivation. This paper will review the role of the p75NTR, critically discuss the impact and implications of this research as the bridge for sleep research and neurological diseases.

To better understand the shape memory materials and self-healing materials, a new series of liquid-crystalline shape memory polyurethane (LC-SMPU) composites, named SMPU-OOBAm, were successfully prepared by incorporating 4-octyldecyloxybenzoic acid (OOBA) into the PEG-based SMPU. The effect of OOBA on the structure, morphology and properties has been carefully investigated. The results demonstrate that SMPU-OOBAm have liquid crystalline properties, triple-shape memory properties and self-healing properties. The incorporated OOBA promotes the crystallizability of both soft and hard segments of SMPU, and the crystallization rate of the hard segment of SMPU decreases when the OOBA-content increases. Additionally, the SMPU-OOBAm forms a two-phase separated structure (SMPU phase and OOBA phase), and it shows two-step modulus changes upon heating. Therefore, the SMPU-OOBAm shows triple-shape memory behavior, and the shape recovery ratio decreases with an increase in the OOBA content. Finally, SMPU-OOBAm shows self-healing properties. The new mechanism can be ascribed to the heating-induced “bleeding” of OOBA in the liquid crystalline state and the subsequent re-crystallization upon cooling. This successful combination of liquid crystalline properties, triple-shape memory properties and self-healing properties make the SMPU-OOBAm composites with many promise applications in smart optical devices, smart electronic devices and smart sensors.

Using a safe subset of C++ is a promising direction for increasing the safety of the programming language while maintaining its performance and productivity. In this paper, we examine how close existing C/C++ code is to conforming to a safe subset of C++. We examine the rules presented in existing safe C++ standards and safe C++ subsets. We analyze the code characteristics of 5.8 million code samples from the Exebench benchmark suite and 5 modern C++ applications using a static analysis tool. We find that raw pointers, unsafe casts, and unsafe library functions are used in both C++ code at large and modern C++ applications. In general, C++ code at large does not differ much from modern C++ code, and continued work will be required to transition from existing C/C++ code to a safe subset of C++.

This paper describes a memory model with 3 levels of information. The lower-level stores source data, is Markov-like and unweighted. Then a middle-level ontology is created from a further 3 phases of aggregating source information, by transposing from an ensemble to a hierarchy at each level. The ontology is useful for search processes and the aggregating process transposes the information from horizontal set-based sequences to more vertical typed-based clusters. The base memory is essentially neutral, where any weighted constraints or preferences should be sent by the calling module. This therefore allows different weight sets to be imposed on the same linking structure. The success of the ontology typing is open to interpretation, but the author would suggest that when clustering text, the result was types based more on use and context, for example, 'linking' with 'structure' or 'provide' with 'web,' for a document describing distributed service-based networks. This allows the system to economise over symbol use, where links to related symbols will be clustered together. The author then conjectures that a third memory substrate would be more neural in nature and would include functions or operations to be performed on the data, along with related memory information.

Unlike animals, persistent dynamic environmental perturbations threaten plants, as they are sessile. Plants keep an inbuilt database of all epigenetic episodes during their lifetime. Present knowledge for exploiting information about how the gene network of plants contributes to epigenetic memory needs to be improved, and extensive in-depth studies are needed. Data from epigenetic memories imparts intelligent behaviour to plants, and these memories can be decoded further to investigate how these plants respond when the same abiotic stress recurs. The epigenetic phenomenon refers to gene expression patterns, including vital factors such as nucleic acids (small ribonucleic acids), histones modelling and methylation of DNA. These changes are cell cycle-associated events that may be transmitted to successive generations. Epigenetic memories due to abiotic stress are necessary for maintaining healthy ecophysiological behaviour of plants and impart the tendency to resist and adapt to challenging environmental conditions. These intelligent memories can be stored and interpreted to prepare for future challenges.

Abstract: Background: Restless Legs Syndrome /Willis-Ekbom disease (RLS/WED) has occasionally -but not consistently- been associated with cognitive, and most notably, language and executive impairment. The present study was conducted to investigate the cognitive trajectories of older individuals with RLS/WED. Methods: Participants were drawn from the randomly selected, older (>64 years), population-based HELIAD cohort. Individuals without dementia, with available neuropsychological evaluations at baseline and follow-up were considered for potential eligibility. A comprehensive assessment examining five principal components of cognition (memory, visuo-spatial ability, attention, executive function, and language) was administered to the partici-pants. Generalized estimating equations analysis was used to examine the unadjusted and adjusted (for critical factors and covariates) effects of RLS/WED on cognition over time. Results: A total of 1003 predominantly female, older (72.9 ±4.9 years) partici-pants, with follow-up evaluations after a mean of 3.09 ±0.85 years and without demen-tia at baseline and follow-up were included in the present study. Among them, 81 were diagnosed with RLS/WED at baseline. Global cognition, memory, attention, executive and visuo-perceptual skills did not differ between those with and without RLS/WED. However, the RLS/WED group performed worse on language at baseline by 0.249 of a standard deviation, while demonstrating a mitigated language decline over time, by 0.063 of a standard deviation. The unadjusted models yielded similar results. Conclu-sions: Our findings were indicative of a baseline language disadvantage among older individuals with RLS/WED, but the initial discrepancy tends to dissolve over time.

Conclusive evidence that specic long-term memory formation relies on den- dritic growth and structural synaptic changes has proven elusive. Connec- tionist models of memory based on this hypothesis are confronted with the so-called plasticity stability dilemma or catastrophic interference. Other fun- damental limitations of these models are the feature binding problem, the speed of learning, the capacity of the memory, the localisation in time of an event and the problem of spatio-temporal pattern generation. This paper suggests that the generalisation and long-term memory mechanisms are not correlated. Only the development and the improvement of the feature ex- tractors in the cortex involves structural synaptic changes. We suggest the long-term memory has a separate mechanism which involves protein synthe- sis to encode the information into the structure of these proteins. A model of memory should be capable of explaining the dierence between memorisation and learning. Learning has in our approach two dierent mechanisms. The generalisation in the brain is handled by the proper development of the links between neurons via synapses. The Hebbian learning rule could be applied only for this part of learning. Storing an internal ring pattern involves, in our approach, a new mechanism which puts the information regarding this ring pattern into the structure of special proteins in such a way that it can be retrieved later. The hypotheses introduced in this article includes a physiological assumption which has not been yet verified because it is not currently experimentally accessible. Keywords: Waves, Protein Synthesis, Resonance, Long Term Memory Preprint submitted to Neural Networks

Human addiction, as a learned behaviour, has and is constantly being treated psychologically, with specific and timely interventions from Neuroscience. We endorse that human addiction can receive further boost as regards treatment, when we firmly understand how it works from a quantum scale. This is majorly because the dopaminergic pathway (DP) that is well elaborated in the brain of every addict is connected to the memory pathway. This further implies that the recall process in the brain of the addict, as regards his/her addiction is fully functional in line with the pleasure that arises from the element of his/her addiction. This dopamine-led pathway shows itself as prominent in what pertains to addiction, this is because of the role it plays in reward. As a neurotransmitter, dopamine flickers when reward is in the offing. It should be noted that a full understanding of the dimensions of addiction in the human person has not be attained to, therefore, we seek to add to this ongoing research, by considering excerpts arising from Quantum Field Theory. We are introducing excerpts from QFT, because DP, is an attendant element in the process of reward and motivation. In clear terms, we are alluding that it all begins with the memory.

This paper deals with the analysis of trends in road accidents on major highways in Brazil. Using updated time series techniques, our results indicate that a low degree of long memory was detected in the series with shocks having transitory effects over time. We further find that the number of accidents taking place in Brazil has been reducing over time, though in the presence of negative shocks, the recovery is not going to be immediate due to the long memory nature of the data. Despite the absence of relevant investment relating to infrastructure expansion, it is worth mentioning the consolidation of a nationwide tolled road system in Brazil involving concessions to private administrators, alongside more severe traffic laws that can impose limitations on driving licences.

The present study explored the expression of CD62L and CD44 by bovine peripheral blood mononuclear cells (PBMCs) and WC1.1+ γδ T cells under Staphylococcus aureus cell culture stimu-lation. In this study, peripheral blood cells were isolated from ten dairy cows and cocultured with S. aureus. Afterward, the γδ T cell subpopulation and the expression of CD44, CD62L and prolif-erative (Ki67+) cells were evaluated by flow cytometry. Our results showed that the percentages of proliferative PBMCs and WC1.1+ γδ T cells were higher when stimulated with S. aureus. The percentage of CD44+ cells increased in S. aureus-stimulated cultured PMBCs and WC1.1+ γδ T cells, as did the CD44 geometric mean fluorescence intensity (GMFI). The rate of CD62L cells did not differ among groups for either PBMCs or WC1.1+ γδ T cells. A higher GMFI of CD62L in prolif-erative PBMCs than nonproliferative PBMCs upon stimulation with S. aureus was detected, whereas no impact on the GMFI of CD62L was observed in WC1.1+ cells. In summary, our study identified that S. aureus was associated with high expression of CD44 in overall PBMCs and WC1.1+ γδ T cells, and they could generate memory WC1.1+ γδ T cells, preferably central memory cells.

Twice-exceptional learners face a unique set of challenges arising from the intersection of extraordinary talent and disability. Neurobiology research has the capacity to complement pedagogical research and provide support for twice-exceptional learners. Very few studies have attempted to specifically address the neurobiological underpinnings of twice-exceptionality. However, neurobiologists have built a broad base of knowledge in nervous system function spanning from the level of neural circuits to the molecular basis of behavior. It is known that distinct neural circuits mediate different neural functions, which suggests that 2e learning may result from enhancement in one circuit and disruption in another. Neural circuits are known to adapt and change in response to experience, a cellular process known as neuroplasticity. Plasticity is controlled by a bidirectional connection between the synapse, where neural signals are received, and the nucleus, where regulated gene expression can return to alter synaptic function. Complex molecular mechanisms compose this connection in distinct neural circuits, and genetic alterations in these mechanisms are associated with both memory enhancements and psychiatric disorder. Understanding the consequences of these changes at the molecular, cellular, and circuit levels will provide critical insights into the neurobiological bases of twice-exceptional learning.

We address the dynamics of two-dimensional Navier-Stokes models with infinite delay and hereditary memory, whose kernels are a much larger class of functions than the one considered in the literature, on a bounded domain. We prove the existence and uniqueness of weak solutions by means of Faedo-Galerkin method. Moreover, we establish the existence of global attractor for the system with the existence of a bounded absorbing set and asymptotic compact property.

Although working memory (WM) is crucial for intellectual abilities, not much is known about its brain underpinnings, especially the structural connectivity. We used diffusion tensor imaging (DTI) to look across the whole brain for the white matter integrity correlates of the individual differences in the reading span (verbal WM capacity during reading) in healthy adults. Right-handed healthy native Russian speakers (N = 67) underwent DTI on a 3T Philips Ingenia scanner. Verbal WM was assessed with the Daneman-Carpenter reading span test (Russian version). Fractional anisotropy maps from each participant were entered into the group tract-based spatial statistics analysis with the reading span as a covariate; the results were TFCE-corrected. After taking into account effects of age, sex, education and handedness, reading span positively correlated with the white matter integrity in multiple sites: the body, the genu and the splenium of corpus callosum; bilateral corona radiata (anterior, posterior, and superior); bilateral superior longitudinal fasciculus; several tracts in the right hemisphere only, including the internal and external capsule; bilateral superior parietal and frontal white matter. Although the left hemisphere is central for verbal processing, we revealed the important role of the right hemisphere white matter for the verbal WM capacity. Our finding indicates that larger verbal working memory span may originate from additional processing resources of the right hemisphere.

Long-Term Potentiation(LTP) and Long-Term Depression(LTD) are two major forms of synaptic plasticity, which are also two well-know functional and unit activities involved in high advanced central neural system(CNS) activities, like memory. But we still know little about how the advanced CNS activities are organized in the brain and in the level of organism. Based on the current understanding and experimental evidence of neurology, we propose the term “Information Circulation” to summarize the current understandings for advanced CNS activities, and we define it as separately input neural signals finally converge in different levels of CNS and interact with each other, then neural information are circulated and processed in different levels of CNS to give out orders for next body actions. This review provides a detailed description for the functional organizations of advanced CNS activities in the term of Information Circulation. This article outlines the receiving of outside stimulation and transmission of neural information, especially transmission and procession of visual bioelectrical signals, then we described neural circuits of Information Circulation in advanced CNS activities, the corresponding specificity and dynamic properties of neural circuits, different sensation linkages, and neural synchronization for information circulation to produce consciousness in CNS. In conclusion, Information Circulation is defined as an important signature involved in advanced CNS activities.

The developmental phase of adolescence is characterized by a multitude of neurocognitive and psychosocial changes and is therefore considered one of the most critical developmental periods of life. Experimentation on the use of substances often begins in adolescence and so does the addiction process. Most research in human subjects shows that chronic cannabis abuse is the cause of the impairment of some cognitive functions, affecting the performance on divided attention, verbal memory and working memory. In this study, we wanted to investigate how the abuse of cannabis (chronic, occasional and absence use) can influence global cognitive functioning, also through executive functions. From the statistical analyzes of our study, it emerges that the group of subjects who use chronic cannabis (group 1) has a significant drop in working memory tasks compared to the group that does not use it (group 3). In addition, the goal of future studies by our group is to verify the permanent alteration of cognitive processes affected through revaluations with calendar follow-up (controlled).

The “memory of water” experiments suggested the existence of molecular-like effects without molecules. Although no convincing evidence of modifications of water – specific of biologically-active molecules – has been reported up to now, consistent changes of biological systems were nevertheless recorded. We propose an alternate explanation based on classical conditioning of the experimenter. Using a probabilistic model, we describe not only the biological system, but also the experimenter engaged in an elementary dose-response experiment. We assume that during conventional experiments involving genuine biologically-active molecules, the experimenter is involuntarily conditioned to expect a pattern, namely a relationship between descriptions (or “labels”) of experimental conditions and corresponding biological system states. The model predicts that the conditioned experimenter could continue to record the learned pattern even in the absence of the initial cause, namely the biologically-active molecules. The phenomenon is self-sustained because the observation of the expected pattern reinforces the initial conditioning. A necessary requirement is the use of a system submitted to random fluctuations with autocorrelated successive states (no forced return to the initial position). The relationship recorded by the conditioned experimenter is, however, not causal in this model because blind experiments with an “outside” supervisor lead to a loss of correlations (i.e., system states randomly associated to “labels”). In conclusion, this psychophysical model allows explaining the results of “memory of water” experiments without referring to water or another local cause. It could be extended to other scientific fields in biology, medicine and psychology when suspecting an experimenter effect.

Nervous systems and brains’ computational abilities are an evolutionary innovation, specializing and speed-optimizing ancient biophysical dynamics. Bioelectric signaling originated in cells’ communication with the outside world and with each other, in order to cooperate toward adaptive construction and repair of multicellular bodies. Here we review the emerging field of developmental bioelectricity, which links the field of basal cognition to state-of-the-art questions in regenerative medicine, synthetic bioengineering, cognitive science, and even machine learning and artificial intelligence. One of the predictions of this view is that regeneration and regulative development are able to restore correct large-scale anatomies from diverse starting states because, like the brain, they exploit bioelectric encoding of distributed goal states - in this case, pattern memories. Based on this idea, we propose a new interpretation of recent stochastic regenerative phenotypes in planaria, by appealing to computational models of memory representation and processing in the brain. Moreover, we discuss novel findings showing that bioelectric changes induced in planaria can be stored in tissue for over a week, thus revealing that somatic bioelectric circuits in vivo can implement a long-term, re-writable memory medium. A consideration of the mechanisms, evolution, and functionality of basal cognition makes novel predictions and provides an integrative perspective on the evolution, physiology, and biomedicine of information processing in vivo.

Shape Memory Alloy (SMA) have emerged as a revolutionary material that holds the potential to change the design and construction methods of buildings and other structures. One of the most promising applications of SMAs in civil engineering is their use as reinforcements for steel structures. This paper presents the latest research progress, opportunities and challenges of SMA in the field of steel structural reinforcement, both in terms of basic components and applications. In terms of components, the construction forms and working mechanisms of Fe-SMA strips, SMA/CFRP composite patches and SMA dampers are introduced. On this basis, the application of SMA in steel structures reinforcement is introduced, and its effect is analyzed from three aspects: crack restoration, seismic retrofitting and structural strengthening. Finally, the results of the current research are summarized and the shortcomings are analyzed, hoping to provide a reference for the research of SMA in the field of steel structures reinforcement.

Deep reinforcement learning is one of the research hotspots in artificial intelligence and has been successfully applied in many research areas, however, the low training efficiency and high demand for samples are problems that limit the application To address these problems, a hierarchical episodic control model extending episodic memory to the domain of hierarchical reinforcement learning is proposed in this paper. The model is theoretically justified and employs a hierarchical implicit memory planning approach for counterfactual trajectory value estimation. Starting from the final step and recursively moving back along the trajectory, a hidden plan is formed within the episodic memory. Experience is aggregated both along trajectories and across trajectories, and the model is updated using a multi-headed backpropagation similar to bootstrapped neural networks. This model extends the parameterized episodic memory framework to the realm of hierarchical reinforcement learning and is theoretically analyzed to demonstrate its convergence and effectiveness. Experiments conducted in Four Room, Mujoco, and UE4-based active tracking , highlight that the hierarchical episodic control model effectively enhances training efficiency. It demonstrates notable improvements in both low-dimensional and high-dimensional environments, even in cases of sparse rewards.

The first appearance of viruses can date back to the late last century. As an effective form of malware, viruses reside in the permanent storage of target hosts. Before a virus can execute, that must load into memory from the persistent storage included in the associated file. Due to the reliable destructive power of viruses, many mechanisms have been developed to defend computer systems against these hazardous threats. Antivirus software is one of the most famous and popular among these mechanisms. Most antivirus software uses static analysis (signature-based) technology on files stored in permanent storage, such as hard disks or USB flashes, to detect viruses hidden in files. Fileless malware was developed to enhance the survivability of malware by circumventing detection. Fileless malware only exists in the target hosts’ memory, not files. Antivirus software cannot even access the fileless malware code, much less analyze it, since it may be performed in memory directly without needing to load it from a disk. As a result, it is difficult for an antivirus engine to defend a system against fileless malware attacks. This paper proposes a kernel-based solution called Check-on-Execution (CoE) to detect fileless malware on a Linux system. When a program is going to execute a piece of code in a writable and executable memory area of a process, CoE suspends the code execution first. Coe retrieves the code from memory, packs the code with an ELF header to create an ELF file, and uses VirusTotal to check the file to prevent a Linux system from executing fileless malware. Experimental results show that CoE noticeably enhances the ability of a Linux system to defend itself again fileless malware. CoE is also suitable for protecting a system from shell code injection attacks, such as buffer and heap overflow attacks. It is capable of handling even packed malware. But in this paper, we only focus on fileless malware.

Inflammatory activation within the brain was linked to a decrease in cognitive abilities, however the molecular mechanisms implicated in the development of inflammatory-related cognitive dysfunction and its prevention are poorly understood. This study compared responses of hippocampal transcriptomes 3 months after the striatal infusion of lipopolysaccharide, alone (LPS; 30 µg) resulting in memory loss, or with dexamethasone (DEX; 5 mg/kg intraperitoneal) pretreatment, which abolished the long-term LPS-induced memory impairment. After LPS alone, a significant elevation in the expression of immunity/inflammatory-linked genes, including chemokine (Cxcl13), cytokines (Il1b, Tnfsf13b), and major histocompatibility complex (MHC) class II members (Cd74, RT1-Ba, RT1-Bb, RT1-Da, RT1-Db1) was revealed. DEX pretreatment did not change expression of these genes, but significantly affected expression of genes encoding ion channels, primarily calcium and potassium channels, regulators of glutamate (Slc1a2, Grm5, Grin2a) and GABA (Gabrr2, Gabrb2) neurotransmission which enriched in such GO biological processes as “Regulation of transmembrane transport”, “Cognition”, “Learning”, “Neurogenesis”, and “Nervous system development”. Taken together, the data suggest that: (1) pretreatment with DEX did not markedly affect LPS-induced prolonged inflammatory response; (2) DEX pretreatment can affect processes associated with glutamatergic signaling and nervous system development, possibly involved by that in the recovery of memory impairment induced by LPS

(1) Background: Many processes play a key role in how language functions, and these processes are strongly related to reading. The aim of our research was to explore the relationship between reading impairment associated with adult acquired cognitive-linguistic impairment (aphasia) and the components of verbal working memory involved in language functioning. (2) Methods: We measured the reading abilities of a total of twenty-two adults diagnosed with aphasia using the Adult Acquired Reading Assessment. To assess working memory, we applied the measurement procedures available in Hungarian for measuring verbal working memory. Correlation analyses were performed to investigate the relationship between reading and the components of working memory involved in processing verbal information. In order to explore this relationship as comprehensively as possible, the results were analysed quantitatively through group-level analyses and qualitatively through case studies. (3) Results: The results suggest that the functioning of phonological short-term memory and verbal working memory is crucial for the reading of vowels, for certain word reading sub-processes such as reading complex words and pseudowords, and for text comprehension tasks, in particular for the processing of implicit text-level infor-mation. (4) Conclusions: The data support a strong relationship between reading and working memory, but not all mechanisms are related with the same weighting. The data will contribute to the understanding of the relationship between reading and working memory, which is important in order to see which cognitive components are dominant in reading instruction and which other cognitive mechanisms are affected in poor readers.

Recent research has suggested that working memory training interventions may benefit children with Developmental Language Disorder (DLD). The current study investigated a short and engaging adaptive working memory intervention that targeted executive skills and aimed to improve both language comprehension and working memory abilities in children with DLD. Forty-seven 6- to 10-year-old children with DLD were randomly allocated to an executive working memory training intervention (n=24) or an active control group (n=23). A pre-test/intervention/post-test/9-month-follow-up design was used. Outcome measures included assessments of language (to evaluate far transfer of the training) and working memory (to evaluate near transfer of the training). Hierarchical multiple regression analyses controlling for pre-intervention performance and age found group to be a significant predictor of sentence comprehension and of performance on six untrained working memory measures at post-intervention and 9-month follow-up. Children in the intervention group showed significantly higher language comprehension and working memory scores at both time points than children in the active control group. The intervention programme showed potential to improve working memory and language comprehension in children with DLD and demonstrated several advantages: it involved short sessions over a short period; caused little disruption in the school day; and was enjoyed by children.

The purpose of this study was to explore the association of cognition with hazardous drinking and alcohol related disorder in persons with bipolar disorder (BD). The study population included 1,268 persons from Finland with bipolar disorder. Alcohol use was assessed through hazardous drinking and alcohol related disorder including alcohol use disorder (AUD). Hazardous drinking was screened with the AUDIT-C (Alcohol Use Disorders Identification Test for Consumption) screening tool. Alcohol related disorder diagnoses were obtained from the national registrar data. Participants performed two computerized tasks from the Cambridge automated neuropsychological test battery (CANTAB) on tablet computer: the 5-choice serial reaction time task, or, reaction time (RT) test and the Paired Associative Learning (PAL) test. Association between RT-test and alcohol use was analyzed with log-linear regression, and eβ with 95% confidence intervals (CI) are reported. PAL first trial memory score was analyzed with linear regression, and β with 95% CI are reported. PAL total errors adjusted was analyzed with logistic regression and odds ratios (OR) with 95% CI are reported. After adjustment for age, education and housing status, hazardous drinking was associated with lower median and less variable RT in females while AUD was associated with a poorer PAL test performance in terms of the total errors adjusted scores in females. Our findings of positive associations between alcohol use and cognition in persons with bipolar disorder are unique.

Background: Alzheimer’s disease affecting about 24 million people world-wide. The socio-economic burden on world-economies costing more than 172 billion US $ annually for the US alone. Objectives: To prepare aqueous extract of T. foenum graecum seeds (FSE) to explore the possible treatment for cognitive deficit in experimental animals. Materials and methods: FSE was subjected to preliminary phytochemical evaluation and antioxidant effect using free radical scavenging method (DPPH). All the animal behavior was video recorded with no human intervention during observation and animal groupings were blinded to avoid investigator bias. Different doses of FSE (5%, 10% and 20%), control, standard (Piracetam, 200 mg/kg, IP.) were given for male albino mice a period of 15 days followed by cognitive assessment in elevated plus maze and novel objection recognition tests. Ttransfer latencies and time exploring novel and familiar objects were recorded in respective tests. Retention of this learned-task was examined again 24 h later and inflexion ratio (IR) and discriminative index (DI) were calculated respectively. Next in the second set of experiment same groups and treatments were continued but scopolamine was administered to all the groups except normal control one hour after the last dose and examined similarly. Results: FSE showed potential antioxidant effect and a dose dependent increase in transfer latency and improved DI indicating a nootropic effect. FSE at 20% showed significant reversal of scopolamine induced dementia in the second set of experiment. Conclusion: FSE improved memory as well as reversed the chemically induced memory deficits in experimental mice.

This paper develops the mathematical modeling and deflection control of a textile-reinforced composite integrated with shape memory actuators. The model of the system is derived using identification method and unstructured uncertainty approach. Based on this model and robust stability analysis a robust proportional-integral controller is designed for controlling the deflection of the composite. The performance of the proposed controller is compared with a classical one through experimental analysis.

Eye movements support memory encoding by binding distinct elements of the visual world into coherent representations. However, the role of eye movements in memory retrieval is less clear. We propose that eye movements play a functional role in retrieval by reinstating the encoding context. By overtly shifting attention in a manner that broadly recapitulates the spatial locations and temporal order of encoded content, eye movements facilitate access to, and reactivation of, associated details. Such mnemonic gaze reinstatement may be obligatorily recruited when task demands exceed cognitive resources, as is often observed in older adults. We review research linking gaze reinstatement to retrieval, describe the neural integration between the oculomotor and memory systems, and discuss implications for models of oculomotor control, memory, and aging.

Studies into the cognitive effects of alcohol have been mixed. They also present methodological challenges, often relying on self-report of alcohol consumption leading to hangover. The current study used BAC (obtained via breathalyser) and self-reported drinking behavior during a night out and related these to hangover severity and cognitive function measured over the internet in the same subjects the following morning. Volunteers were breathalysed and interviewed as they left a central entertainment district of an Australian state capital. They were provided with a unique identifier and, the following morning, logged on to a website. This included an online version of the Alcohol Hangover Severity Scale (AHSS), and number and type of drinks consumed the previous night and the eTMT-B - a validated, online analogue of the Trail Making Test B of executive function and working memory. Hangover severity was significantly correlated with one measure only, namely the previous night’s BAC (r = .228, p = .019). Completion time on the eTMT-B was significantly correlated with hangover severity ( r = .245, p = .012), previous night’s BAC (r = .197, p = .041) and time spent dinking (r = .376, p < .001). These findings confirm that alcohol hangover negatively affects cognitive functioning and that poorer working memory and executive performance correlates with hangover severity. The results also support the utility of using online measures in hangover research.

Background: The Apolipoprotein E4 (ApoE4) genotype is strongly associated with Alzheimer’s disease (AD), although the presence of the ApoE4 allele alone is not sufficient to explain AD. The pathophysiology of amnestic mild cognitive impairment (aMCI) remains unclear. This study aims to examine associations between peripheral blood biomarkers coupled with ApoE4 and episodic and semantic memory. Methods: The CERAD battery was completed and various biomarkers were assayed in 60 subjects with aMCI, 60 with AD and 62 healthy controls. Results: Deficits in semantic and episodic memory were significantly predicted by anion gap and bicarbonate, albumin and glucose coupled with Apo E4. Furthermore, these peripheral biomarkers interacted with ApoE to predict greater memory impairments. Conclusions: Peripheral blood biomarkers may interact with pathways related to ApoE4 to predict greater semantic and episodic memory impairments, thus contributing to the pathophysiology of aMCI and AD. Our data suggest that the transition from aMCI to AD could at least in some cases be associated with significant interactions between ApoE4 and those peripheral blood biomarkers.

Considering the isotropic release process of nanoelectromechanical systems (NEMS), defining the active region of NEM memory switches is one of the most challenging process technologies for the implementation of monolithic-three-dimensional (M3D) CMOS-NEM hybrid circuits. In this paper, we propose a novel encapsulation method of NEM memory switches. It uses alumina (Al2O3) passivation layers which are fully compatible with CMOS baseline process. The Al2O3 bottom passivation layer can protect intermetal dielectric (IMD) and metal interconnection layers from vapor hydrogen fluoride (HF) etch process. Thus, the controllable formation of the cavity for the mechanical movement of NEM memory switches can be achieved without causing any damage to CMOS baseline circuits as well as metal interconnection lines. As a result, NEM memory switches can be located in any places and metal layers of an M3D CMOS-NEM hybrid chip, which makes circuit design easier and more volume-efficient. The feasibility of our proposed method is verified based on experimental results.

Heavy caffeine consumption is associated with adverse health effects. The effects of moderate and high doses of caffeine mixed with drinking water on the motor coordination, learning and memory and the social behavior in mice were studied in mice. Animals were divided into 3 groups: control group, moderate dose group (Ac MD) and high dose group (Ac HD). The animals were tested after 7 days of caffeine administration. Rota rod test for motor coordination showed that the mice of the moderate dose group could stay more time on the rotating rod before they fall than the control group and the high dose group. Water maze test for learning and memory showed better performance of mice receiving moderate dose of caffeine compared to the other groups. Animals that were administered moderate as well as high doses of caffeine showed no sociability and no preference for social novelty in the three-chamber test used to test the social behavior. In elevated plus maze, control animals showed no anxiety- like behavior while mice administered with caffeine were both showing anxiety-like behaviors. We concluded that acute administration of moderate dose of caffeine to mice could enhance their spatial memory and motor coordination. High doses however caused defects in memory and learning. The social behavior as the level of anxiety and sociability was affected negatively by moderate as well as high dose caffeine administration.

Energy consumption of processors and memories is quickly becoming a limiting factor in the deployment of large computing systems. For this reason it is important to understand the energy performance of these processors and to study strategies allowing to use them in the most efficient way. In this work we focus on computing and energy performance of the Knights Landing Xeon Phi, the latest Intel many-core architecture processor for HPC applications. We consider the 64-core Xeon Phi 7230, and profile its performance and energy efficiency using both its on-chip MCDRAM and the off-chip DDR4 memory as the main storage for application data. As a benchmark application we use a Lattice Boltzmann code heavily optimized for this architecture, and implemented using several different arrangements of the application data in memory (data-layouts, in short). We also assess the dependence of energy consumption on data-layouts, memory configurations (DDR4 or MCDRAM), and number of threads per core. We finally consider possible trade-offs between computing performance and energy efficiency, tuning the clock frequency of the processor using the Dynamic Voltage and Frequency Scaling (DVFS) technique.

Benveniste’s experiments – known in the lay press as the “water memory” phenomenon – are generally considered to be a closed case. However, the amount of data generated by twenty years of well-conducted experiments prevents closing the file so simply. An issue, which has been little highlighted so far, merits to be emphasized. Indeed, if Benveniste failed to persuade his peers of the value of his experiments, it was mainly because of a stumbling block, namely the difficulty of convincingly proving the causal relationship between the supposed cause (“informed water”) and the experimental outcomes in different biological models. To progress in the understanding of this phenomenon, we abandon the idea of any role of water in these experiments (“water memory” and its avatars). In other words, we assume that “controls” and “tests” that were evaluated were all physically identical; only their respective designations (labels) differentiated them. Since we state that there is no causal link between labels (“controls” vs. “tests”) and corresponding states of the biological system (no change vs. change), these variables are independent. Therefore, the key question is: “Is it possible to observe a correlation between independent variables that mimics a causal relationship but is itself not causal?” In this article, we show how simple considerations based on probability theory lead to describe non-classical correlations involving the experimenter. This probabilistic modelling allows to propose an alternative explanation to Benveniste’s experiments where water plays no role and where the place of the experimenter is central.

Background: Despite hearing aids adequately compensate for hearing loss, a substantial proportion of the population leave their hearing difficulties untreated. Even though this is a well-known clinical issue, the optimal approach to address this issue during the hearing rehabilitation process is still unclear. Purpose: The present study aims to characterise behavioural and neurophysiological auditory and cognitive processing skills in experienced hearing aid users versus those with normal hearing, aimed at providing clinicians with the evidence required to adequately manage the expectations of their clients, thus indirectly reinforcing hearing-aid adoption within the adult population with hearing loss. Research design: Behavioural tests included auditory, cognitive, and speech-in-noise tasks; and neurophysiological testing included cortical auditory evoked potentials evoked by a /da/ stimulus presented at 65 dB SPL. The tests were selected based on previous literature supporting specific speech-understanding skills. Study sample: Ten participants (7 female, 21—68 years) with bilateral, mild-moderate to moderately-severe sensorineural hearing loss (HL), and 10 with clinically normal hearing (NH, 8 female, 19—62 years) participated in the study. Data collection and analysis: Behavioural data was analysed using multivariate analysis of variance (MANOVA) and neurophysiological analysis used measurements such as independent t-test, time-frequency analysis and inter-trial phase coherence. Results: The NH and HL groups presented similar scores in all the behavioural tasks. Time-frequency analysis revealed a statistically significantly reduction in alpha (8–12 Hz) synchronisation at the centro-frontal electrodes in the HL group – a brain activity pattern that has been associated with listening effort, inhibition and selective attention. Conclusions and significance: Results support the conclusion that hearing aids are effective in compensating for the audibility of their users, enabling them to perform at similar levels than their normal-hearing peers. However, the reduced alpha synchronisation observed in the HL population indicates that adequate audibility does not extend to improved neural responses. Future studies need to investigate the induced activity in speech understanding paradigms to explore the auditory processing differences at cortical level. The results are only from a small sample size but the findings have the potential to support clinicians in managing adequately the expectations of their clients in regards the benefits of hearing aid technologies.

An association of food sources with odors prominently guides foraging behavior in animals. To understand the interaction of olfactory memory and food preferences, we used glucose-averse (GA) German cockroaches. Multiple populations of cockroaches evolved a gustatory polymorphism where glucose is perceived as a deterrent and enables GA cockroaches to avoid eating glucose-containing toxic baits. Comparative behavioral analysis using an operant conditioning paradigm revealed that learning and memory guide foraging decisions. Cockroaches learned to associate specific food odors with fructose (phagostimulant, reward) within only a 1 hr conditioning session, and with caffeine (deterrent, punishment) after only three 1 hr conditioning sessions. Glucose acted as reward in wild type (WT) cockroaches, but GA cockroaches learned to avoid an innately attractive odor that was associated with glucose. Olfactory memory was retained for at least 3 days after three 1 hr conditioning sessions. Our results reveal that specific tastants can serve as potent reward or punishment in olfactory associative learning, which reinforces gustatory food preferences. Olfactory learning therefore reinforces behavioral resistance of GA cockroaches to sugar-containing toxic baits. Cockroaches may also generalize their olfactory learning to baits that contain the same or similar attractive odors even if they do not contain glucose.

Shape-memory hydrogels (SMH) are as multifunctional, actively-moving polymers of interest in biomedicine. In loosely crosslinked polymer networks gelatin chains may form triple helices, which can act as temporary netpoints in SMH, depending on the presence of salts. Here, we show programming and initiation of the shape-memory effect of such networks based on a thermomechanical process compatible with the physiological environment. The SMH were synthesized by reaction of glycidylmethacrylated gelatin with OEG α,ω-dithiols of varying crosslinker length and amount. Triple helicalization of gelatin chains is shown directly by wide-angle X-ray scattering and indirectly via the mechanical behavior at different temperatures. The ability to form triple helices increased with the molar mass of the crosslinker. Hydrogels had storage moduli of 0.27-23 kPa and Young’s moduli of 215-360 kPa at 4 °C. The hydrogels were hydrolytically degradable, with full degradation to water soluble products within one week at 37 °C and pH = 7.4. A thermally-induced shape-memory effect is demonstrated in bending as well as in compression tests, in which shape recovery with excellent shape recovery rates Rr close to 100% were observed. In the future, the material presented here could be applied e.g. as self-anchoring devices mechanically resembling the extracellular matrix.

Alcohol and nicotine are widely-abused legal substances worldwide. Relapse to alcohol or tobacco seeking and consumption after abstinence is a major clinical challenge, and is often evoked by cue-induced craving. Therefore, disruption of the memory for the cue-drug association is expected to suppress relapse. Memories have been postulated to become labile shortly after their retrieval, during a “memory reconsolidation” process. Interference with the reconsolidation of drug-associated memories has been suggested as a possible strategy to reduce or even prevent cue-induced craving and relapse. Here, we surveyed the growing body of studies in animal models and in humans assessing the effectiveness of pharmacological or behavioral manipulations in reducing relapse by interfering with the reconsolidation of alcohol and nicotine/tobacco memories. Our review points to the potential of targeting the reconsolidation of these memories as a strategy to suppress relapse to alcohol drinking and tobacco smoking. However, we discuss several critical limitations and boundary conditions, which should be considered to improve the consistency and replicability in the field, and for development of an efficient reconsolidation-based relapse prevention therapy.

The present work studies a swelling porous-elastic system with viscoelastic damping. We establish a general and optimal decay estimate which generalizes some recent results in the literature. Our result is established without imposing the usual equal-wave-speed condition associated with similar problems in literature.

In this era of technology, programming has become more significant than ever before. Python and C++ are both widely used programming languages. Python, the most popular programming language in today’s world, is a high-level object-oriented language whereas C++, the language behind most operating systems, is a low-level object-oriented language. In this paper, we present a comparative study of Python and C++. This paper discusses the introduction to these languages, their memory management techniques, and the reasons behind their program execution speed. Furthermore, we analyzed the execution time and memory used by multiple algorithms in both the languages with best, average, and worst cases. They are also compared with respect to the benefits and issues related to them. Results indicate that C++ is faster than Python in execution speed but Python serves as a better language for beginners due to its simplicity. Moreover, for the best results, the language should be selected according to the type of project.

This paper studies long economic series to assess the long-lasting effects of pandemics. We analyze if periods of time that cover pandemics have a change in trend and persistence in growth, and in level and persistence in unemployment. We find that there is an upward trend in the persistence level of growth across the centuries. In particular, shocks originated by pandemics in recent times seem to have permanent effect in growth. Moreover, our results show that the unemployment rate increases and it becomes more persistent after a pandemic. In this regard, our findings support the design and implementation of counter-cyclical policies to soften the shock of the pandemic.

Dry eye syndrome (DES) has become increasingly prevalent due to the prolonged use of digital devices in modern society. Individual supplementation with lutein or docosahexaenoic acid (DHA) demonstrated potential benefits for eye health. This study aimed to investigate the effects of lutein plus DHA complex supplementation on DES, visual function, and memory in healthy individuals. Thirty-four participants, aged 40~60 years, received lutein/DHA complex supplements (containing 10 mg free-form lutein, 200 mg DHA, 30 mg red algae extract (astaxanthin), phosphatidylserine, and vitamin A) for 12 weeks. Ophthalmological examinations and memory tests were carried out, and a questionnaire was administered at weeks 0, 6, and 12 of the study. After 12 weeks of the intervention, the tear break-up time had significantly increased, and intraocular pressure (IOP) had significantly decreased. This suggests that lutein/DHA complex supplementation may reduce the IOP and offer potential benefits for DES, as indicated by improved tear stability.

Brain hemispheres develop rather symmetrically except in the case of pathology or intense training. As school experience is a form of training, the current study tested the influence of pedagogy on morphological development through the cortical thickness (CTh) asymmetry index (AI). First, we compared CTh AI of 111 students aged 4 to 18 with 77 adults aged > 20. Second, we investigated CTh AI in the students, as a function of schooling background (Montessori or traditional). At the whole-brain level, CTh AI was not different between the adult and student groups, even when controlling for age. However, the pedagogical experience was found to impact CTh AI in the temporal lobe, within the parahippocampal (PHC) region. The PHC has a functional lateralization, with the right PHC having a stronger involvement in spatiotemporal context encoding, while the left PHC is involved in semantic encoding. We observed CTh asymmetry toward the left PHC for participants enrolled in Montessori schools and toward the right for participants enrolled in traditional schools. As these participants were matched on age, intelligence, home life, and socioeconomic conditions, we interpret this effect found in memory-related brain regions to reflect differences in learning strategies. Pedagogy modulates how new concepts are encoded, with possible long-term effects on knowledge transfer.

Nature provides plenty of good examples for simple and very efficient joint assemblies. One example is the enormously flexible cervical spine of American barn owls, which consists of 14 cervical vertebrae. Each pair of vertebrae produces a comparatively small individual movement in order to provide a large overall movement of the entire cervical spine. The biomimetic replication of such joints is difficult due to the delicate and geometric unrestricted joint shapes as well as the muscles that have to be mimicked. Using X-ray as well as micro computed tomography images and with the utilisation of additive manufacturing, it is possible to produce the owl neck vertebrae in scaled-up form, to analyse them and then to transfer them into technically usable joint assemblies. The muscle substitution of these joints is realised by smart materials actuators in the form of shape memory alloy wire actuators. This actuator technology is outstanding for its muscle-like movement and for its enormous energy density [1,2]. The disadvantage of this wire actuator technology is the low rate of contraction, which means that a large length of wire has to be installed to generate adequate movement. For this reason, the actuator wires are integrated into additively manufactured carrier components to mimic the biological joints. This results in joint designs that compensate for the disadvantages of the small contraction of the actuators by intelligently installing large wire lengths on comparatively small installation spaces, while also providing a sufficient force output. With the help of a test rig, the developed technical joint variants are examined and evaluated. This demonstrates the technical applicability of this bionic joints.

The dynamics of suspended sediment involves inherent non-linearity and complexity as a result of the presence of both spatial variability of the basin characteristics and temporal climatic patterns. As a result of this complexity, the conventional sediment rating curve (SRC) and other empirical methods produce inaccurate predictions. Deep neural networks (DNNs) have emerged as one of the advanced modeling techniques capable of addressing inherent non-linearity in hydrological processes over the last few decades. DNN algorithms are used to perform predictive analysis and investigate the interdependencies among the most pivotal water quantity and quality parameters i.e., discharge, suspended sediment concentration (SSC), and turbidity. In this study, the Long short-term memory (LSTM) algorithm of DNNs is used to model the discharge-suspended sediment relationship for the Stony Clove Creek. The simulations were run using primary data on discharge, SSC and turbidity. For the development of the DNN models and examining the effects of input vectors, combinations of different input vectors (namely discharge, and SSC) for the current and previous days are considered. Furthermore, a suitable modelling approach with an appropriate model input structure is suggested based on model performance indices for the training and testing phases. The performance of developed models is assessed using statistical indices such as root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). Statistically, the performance of DNN-based models in simulating the daily SSC performed well with observed sediment concentration series data. The study demonstrates the suitability of the DNN approach for simulation and estimation of daily SSC, opening up new research avenues for applying hybrid soft computing models in hydrology.

This article presents the implementation of a model to estimate the future price of commodities in the Brazilian market from time series of short-term technical evaluation. For this, data from two databases were used, one referring to the foreign market (opening values, maximum, minimum, closing, closing adjustment and volume) and the other, from the Brazilian market (the price of the day), considering commodities, sugar, cotton, corn, soybean and wheat. Subsequently, the technical indicators were calculated from the TA-Lib technical analysis library. Pearson’s correlation coefficient was applied, records with low correlation were removed, and then the database was consolidated. From the pre-processed data, Long Short-Term Memory (LSTM) recurrent neural networks were used to perform data prediction at the one and three day interval. These models were evaluated using the mean square error (MSE), obtaining results between 0.00010 and 0.00037 on test data one day ahead, and from 0.00017 to 0.00042 three days ahead. However, based on the results obtained, it was observed that the developed model obtained a promising forecasting performance for all the commodities evaluated. As a main contribution, there is the consolidation of databases that can be used in future scientific research. Furthermore, based on its interpretation, it can assist in decision making regarding the buying and selling of commodities to increase financial gains.

A Shape Memory Alloy (SMA) enabled Overtopping Wave Energy Converter (OWEC) that maximizes its overtopping discharge, and thus energy output under different wave conditions is presented. Among all the parameters affecting the overtopping discharge rate, the crest freeboard height is the most influential one to control the overtopping discharge rate and the stored overtopping volume behind it. Currently, all the OWEC crest freeboard heights are fixed by design to maximize the discharge rate on one particular sea state. In the present study, we show that the SMA can adjust the crest freeboard height through a control system based on the sea state and achieve an optimal overtopping discharge rate. A scaled OWEC model is built in the lab with its crest freeboard height controlled by springs made of SMA. The length (and thus tension) of the springs is controlled by temperature changes by changing the passing current through the springs. By adjusting the length of the springs based on the incoming wave condition, we adjust the freeboard to an optimal height known to generate a maximum overtopping discharge rate for energy conversion. This smart material-enabled design can maximize the overtopping discharge and thus the output power of the OWEC under various wave conditions. Furthermore, the simplicity of using SMA springs as the actuator leads to the minimum number of moving mechanical parts, which can remarkably decrease maintenance costs. As the proof of concept, two types of tests are conducted in the laboratory using the same OWEC model under several random wave trains generated from spectra with different significant wave heights - one type with a fixed crest freeboard height and the other type featuring the adjustable crest freeboard height controlled by the springs. The substantial increase of harvested output power in the OWEC with the adjustable crest freeboard height may pave the way for more efficient wave energy conversion systems.

Working memory refers to the capability of the nervous system to selectively retain short-term memories in an active state. The long-standing viewpoint is that neurons play an indispensable role and working memory is encoded by synaptic plasticity. Furthermore, some recent studies have shown that calcium signaling assists the memory processes and the working memory might be affected by the astrocyte density. Over the last few decades, growing evidence has also revealed that astrocytes exhibit diverse coverage of synapses which are considered to participate in neuronal activities. However, very little effort has yet been made to attempt to shed light on the potential correlations between these observations. Hence, in this article we will leverage a computational neuron-astrocyte model to study the short-term memory performance subject to various astrocytic coverage and we will demonstrate that the short-term memory is susceptible to this factor. Our model may also provide plausible hypotheses for the various sizes of calcium events as they are reckoned to be correlated with the astrocytic coverage.

Executive functions comprise top-down cognitive processes that exert control over information processing, from acquiring information to issuing a behavioural response. These cognitive processes of inhibition, working memory and shifting underpin complex cognitive skills, such as episodic memory and planning, which have been repeatedly investigated in several bird species in recent decades. Until recently, avian executive functions were studied in relatively few bird species, but have gained traction in comparative cognitive research following MacLean and colleagues’ large-scale study (2014). Therefore, in this review paper, relevant previous findings are collected and organized to facilitate further investigations of these core cognitive processes in birds. This review can assist in integrating findings from avian and mammalian cognitive research and further current understanding of executive functions’ significance and evolution.

Ag+ pollution is great of harm to the human body and the biology. Therefore, it is an urgent need to develop inexpensive and accurate detection methods. Herein, lignin-derived structural memory carbon nanodots (CSM-dots) with outstanding fluorescence property were fabricated via a green method, which reserve functional and structural units of the precursor molecules. The CSM-dots could specifically bind Ag+, accompanied with a remarkable fluorescence quenching response. This “turn-off” fluorescence behavior was used for Ag+ determination in a linear range of 5-290 μM with the detection limit as low as 500 nM. Furthermore, the finding showed that this sensing nano-platform was successfully used for Ag+ determination in real samples and intracellular imaging, showing great potential in biological and environmental monitoring applications.

Deep neural networks (DNNs) have made a huge impact in the field of machine learning by providing unbeatable humanlike performance to solve real-world problems such as image processing and natural language processing (NLP). Convolutional neural network (CNN) and recurrent neural network (RNN) are two typical architectures that are widely used to solve such problems. Time sequence-dependent problems are generally very challenging, and RNN architectures have made an enormous improvement in a wide range of machine learning problems with sequential input involved. In this paper, different types of RNN architectures are compared. Special focus is put on two well-known gated-RNN’s Long Term Short Memory (LSTM) and Gated Recurrent Unit (GRU). We evaluated these models on the task of force estimation system in pouring. In this study, four different models including multi-layers LSTM, multi-layers GRU, single-layer LSTM and single-layer GRU) were created and trained. The result suggests that multi-layer GRU outperformed other three models.

Neurological disorders, such as amyotrophic lateral sclerosis, Parkinson’s disease, and Alzheimer’s disease, are commonly associated with persistent neuro-inflammation, and there is an urgent need to discover new therapeutic agents that may target the various pathways involved in neurodegeneration. In this study, we investigated the therapeutic potential of folecitin, a flavonoid isolated from Hypericum oblongifolium, against lipopolysaccharide (LPS)-induced oxidative stress associated with neurodegeneration, amyloidogenic Aβ production pathway, and memory dysfunction in mice. LPS was administered i.p. at 250 µg/kg/day for 3 weeks, followed by the administration of folecitin at a dose of 30 mg/kg/day for the last two weeks. A Western blot technique was used to assess the expression of different proteins involved in oxidative stress, neurodegeneration, and neuronal synapse. Results indicated that folecitin significantly reduced LPS-induced apoptotic neurodegeneration, including the expression of BAX, Caspase-3, and PARP-1 proteins, inhibited BACE1, and the amyloidogenic Aβ production pathway. Folecitin improved both pre- and post-neuronal synapse, as well as memory dysfunction. Furthermore, folecitin significantly activated endogenous antioxidant proteins such as Nrf-2 and HO-1 via stimulating the phosphorylation of Akt proteins. These findings suggest that folecitin may be a suitable lead to design new drugs for neurotoxin-triggered neurodegenerative disorders.

Recent evidence has highlighted the critical role of memory cells in maintaining lifelong food allergies, thereby identifying these cells as therapeutic targets. IgG⁺ memory B cells replenish pools of IgE-secreting cells upon allergen exposure, which contract thereafter due to the short lifespan of tightly regulated IgE-expressing cells. Advances in the detection and highly dimensional analysis of allergen-specific B and T cells from allergic patients have provided insight on their phenotype and function. The newly identified Th2A and Tfh13 populations represent a leap in our understanding of allergen-specific T cell phenotypes, though how these populations contribute to IgE memory responses remains poorly understood. Within, we discuss the mechanisms by which memory B and T cells are activated, integrating knowledge from human systems and fundamental research. We then focus on memory reactivation; specifically, on the pathways of secondary IgE responses. Throughout, we identify areas of future research which will help identify immunotargets for a transformative therapy for food allergy.

Abstract Women victims of abuse can suffer neuropsychological sequelae that affect memory and attention, as well psychopathological disorders such as depression. These consequences affect their daily life and physical and psychological health. Objective: To analyze sequelae that affect attention and memory, as well a possible association of these sequelae to depression. Method: A total of 68 women victims of gender-based violence participated in the study. The participants were between 15 and 62 years of age and resided in Spain at the time of data collection. The Luria DNA Battery (Neuropsychological Diagnosis of Adults) by Manga and Ramos (2000); and the Beck Depression Inventory were applied. Results: Women victims of gender-based violence suffer neuropsychological sequelae, presenting low short-term memory and attentional control; and score low on the Luria-DNA battery. Of these women, 60% suffer from some relevant type of depression, and there are significant differences according to their degree of memory. Through the HJ-Biplot, a direct relationship was found between memory and attentional control with the total score of the Luria battery. On the other hand, an inverse relationship was found between short-term memory and depression. Lastly, three well-differentiated gender clusters of women victims of gender-based violence were identified. Conclusions: A lower rate of depression is observed in women victims of abuse when they have a more intact short-term memory.

Purpose of the study was to explore the association of cognition with hazardous drinking, binge drinking and alcohol use disorder in schizophrenia and schizoaffective disorder. Cognitive deficits are common in schizophrenia. Alcohol might be associated with additional cognitive impairment in schizophrenia patients. The study population included 3362 schizophrenia and schizoaffective disorder patients in Finland. Hazardous drinking was screened with the AUDIT-C (Alcohol Use Disorders Identification Test for Consumption) screening tool. Binge drinking was obtained from the AUDIT-C. Alcohol use disorder (AUD) diagnoses were obtained from the national registrar data. Participants performed two computerized tasks from the Cambridge automated neuropsychological test battery (CANTAB) on tablet computer: the 5-choice serial reaction time task (5-CSRTT), or, reaction time (RT) test and the Paired Associative Learning (PAL) test. Association of alcohol use with RT test and PAL test was analyzed with log-linear regression and logistic regression, respectively. After adjustment for age, education and age at first psychotic episode, hazardous drinking in females was associated with lower median RT. Compared to never binge drinkers, male and female participants drinking 6 or more doses of alcohol monthly or less had lower median RT. In the PAL test both first trial memory score (FTMS) and total errors adjusted score (TEAS) were associated with better performance in males drinking 6 or more doses of alcohol weekly or more and in females drinking 6 or more doses monthly or less. Higher PAL TEAS was associated with AUD in females Some positive associations between alcohol and cognition were found in male and female schizophrenia and schizoaffective disorder patients with hazardous drinking and binge drinking.

Learning dental procedures is a complex task involving the development of fine motor skills. The reported use of theories and/ or evidence for designing learning activities to develop the fine motor skills needed for dental practice is limited. The aim of this review is to explore the available body of knowledge related to learning fine motor skills in dentistry. Evidence from studies investigating motor skill learning highlights the negative impact of self-focus and self-regulation on learning outcomes, particularly during the early stages of learning. The development of activities and schedules that enable novices to demonstrate characteristics similar to experts, without the reported long period of ‘deliberate practice’, is clearly of value. Outcomes of learning implicitly are important in dentistry because working under stressful conditions is common, either during undergraduate study or in practice. It is suggested that learning implicitly in the simulation stage can reduce disrupted performance when transitioning to clinical settings. Therefore, further investigation of effective methods for learning dental fine motor skills is indicated, using approaches that result in robust performance, even under stressful conditions.

Thermal shape memory polymers (SMPs) find increasing applications in biology and medicine due to their promising potential for improved biocompatibility. In such applications, the inevitable penetration of small molecules from the ambient fluid into the polymer influences the shape recovery process and often leads to a reduction of the temperature, at which shape recovery takes place. We show here via molecular dynamics simulations that the size of additive molecules plays a key role for this process. While the effect of concentration on the recovery rate is monotonic in the investigated range, a non-monotonic dependence on the size of additive molecules emerges at temperatures close to the glass transition. This work thus identifies the additives’ size to be a qualitatively novel parameter for switching the recovery process in polymer-based shape memory materials.

Neurodevelopmental disorders arise from genetic and/or from environmental factors and are characterized by different degrees of intellectual disability. The mechanisms that govern important processes sustaining learning and memory, which are severely affected in intellectual disability, have classically been thought to be exclusively under neuronal control. However, this vision has recently evolved into a more integrative conception, in which astroglia, rather than just acting as metabolic supply and structural anchoring for neurons, interact at distinct levels modulating neuronal communication and possibly also cognitive processes. Recently, genetic tools have made it possible to specifically manipulate astrocyte activity unraveling novel functions that involve astrocytes in memory function in the healthy brain. However, astrocyte manipulation has also underscored potential mechanisms by which dysfunctional astrocytes could contribute to memory deficits in several neurodevelopmental disorders revealing new pathogenic mechanisms in intellectual disability. Here, we review the current knowledge about astrocyte dysfunction that might contribute to learning and memory impairment in neurodevelopmental disorders, with special focus on Fragile X syndrome and Down syndrome.

The role of innate immunity in neutralization of viral infections (including COVID-19) and forming long-lasting and specific immune memory is considered. It is assumed that antiviral protection is generated by the mechanism of RNA interference (RNAi) and is based on the presence of specific viral patterns in the DNA library of the host cells.

A premise of statistical learning research is that learners attend to and learn the frequencies of repeating or co-occurring elements in the input. When the input is a series of words, participants readily learn the frequencies of phoneme sequences, that is, to learn phonotactic frequencies. Inherent to the concepts of both frequency and phonotactics is order, or the temporal structure of the input. Order is similarly inherent to statistical learning, yet the effect of order on statistical learning is not well understood. In the present study, adult participants learned the relative frequencies of eight item-medial consonant sequences, for example, the /mk/ in /nʌmkət/. Across five ordering conditions, both familiarization and test stimuli were independently ordered and randomized, thus allowing for a relatively broad search for order effects in an established statistical learning paradigm. Participants learned the target frequencies equivalently across the five ordering conditions, indicating no modulating effect of order. Nevertheless, participants also approached the task by applying idiosyncratic, structured orders to their responses. The result is an unexpected but robust effect of order. Both the results and the design of the study also allow for increased integration of statistical learning with memory and other aspects of cognition.

The mechanization of agricultural activities has led to indiscriminate deposition of toxic xenobiotics, including organophosphates in the biomes, and this has led to intoxication characterized with deleterious oxidative and neuronal changes. This study investigated the consequences of oxidative and neurogenic disruptions that follow exposure to two organophosphates, chlorpyrifos (CPF) and dichlorvos (DDVP) on neuro-cognitive performance and anxiety-like behaviors in rats Thirty-two adult male Wistar rats (150 – 170g) were randomly divided into 4 groups, orally exposed to normal saline (NS), DDVP (8.8mg/kg), CPF (14.9mg/kg) and DDVP+CPF for 14 consecutive days. On day 10 of exposures, anxiety-like behaviors and amygdala dependent fear learning were assessed using Open Field and Elevated Plus Maze paradigms respectively, while spatial working memory was assessed on day 14 in the Morris water maze paradigm, following 3 training trials each on days 11, 12 and 13. On day 15, the rats were euthanized, and their brains excised, hippocampus and amygdala removed, 5 of which were homogenized and centrifuged to analyze nitric oxide (NO) metabolites, total reactive oxygen species (ROS), and acetylcholinesterase (AChE) activity, and the other three processed for histology (cresyl violet stain) and proliferative marker (Ki67 immunohistochemistry). Marked (p≤0.05) loss in body weight, AChE depletion, and overproduction of both NO and ROS were observed after repeated exposure to individual and combined doses of CPF and DDVP. Insults from DDVP exposure appeared more severe owing to the observed greater losses in the body weights of exposed rats. There was also a significant (p≤0.05) effect on the cognitive behaviors recorded from the exposed rats, and these deficits were related to the oxidative damage and neurogenic cell loss in the hippocampus and the amygdala of the exposed rats. Taken together, these results provided an insight that oxidative and neurogenic damages are central to the severity of neuro-cognitive dysfunction and increased anxiety-like behaviors that follow organophosphate poisoning.

In modern Commercial Off-The-Shelf (COTS) multicore systems, cores can produce several simultaneous memory requests. The processing of such requests over the memory controller negatively impacts the interference delay triggered by running parallel tasks on the platform. In this paper, we propose a software-based testing approach for analyzing memory interference delay, when cores are exposed to extensive read/write requests that access in parallel their Cache Coherent Interconnect. The hardware targeted in this work is the well-known LayerScape QorIQ LS2085A, which can be approached as a potential successor to the Freescale QorIQ P4080. The test analysis was conducted based on a bare-metal operating system that we developed to guarantee a deterministic execution environment at all time points. Our testing was accomplished using a set of carefully designed synthetic benchmarks as well as TACLeBench benchmarks.

In The Work of the Dead: A Cultural History of Mortal Remains, Thomas Laqueur argues that the work of the dead is carried out through the living and through those who remember, honour, and mourn the dead. Further, he maintains that the brutal or careless disposal of the corpse “is an attack of extreme violence”. To treat the dead body as if it does not matter or as if it were ordinary organic matter would be to deny its humanity. From Laqueur’s point of view it is inferred that the dead are believed to have rights and dignities that are upheld through rituals, practices, and beliefs of the living. Drawing on dark tourism scholarship and cultural memory theory, this paper examines the display of human bones at Sedlec Ossuary, Czech Republic and the tourist culture that has built up around the site. Primarily, my writing calls into question the commoditization of burial places as a conceivable violation of the human rights of the dead. My research is driven by a number of questions: What is it that draws tourists to burial grounds and how do heritage sites negotiate visitor experiences? What are the ethical boundaries when a final resting place with bodies on display is also marketed as a tourist site? Do the dead have human rights and how are the living responsible for preserving those rights?

In this work, we consider a one-dimensional laminated beam in the case of non-equal wave speeds with only one infinite memory on the effective rotation angle. In this case, we establish the general decay result for the energy of solution without any kind of internal or boundary control. The main result is obtained by applying the method used in Guesmia et al. (Electron. J. Differential Equations 193: 1-45, 2012) and the second-order energy.

In the current paper, a residual generation filter with finite memory structure is proposed for sensor fault detection. The proposed finite memory residual generation filter provides the residual by real-time filtering of fault vector using only the most recent finite observations and inputs on the window. It is shown that the residual given by the proposed residual generation filter provides the exact fault for noise-free systems. The proposed residual generation filter is specified to the digital filter structure for the amenability to hardware implementation. Finally, to illustrate the capability of the proposed residual generation filter, numerical examples are performed for the discretized DC motor system having the multiple sensor faults.

Using recent developments in econometrics and computational statistics we consider the estimation of the instantaneous rate of asset return process when the underlying Data Generating Mechanism (DGM) is an Ornstein-Uhlenbeck process, driven by fractional noise, and sampled at fixed intervals of length h. To address the problem we adopt throughout the paper an exact discretization approach. This enable us to exploit the fact that a flow sampling scheme arises naturally when observing the DGM. For, while the instantaneous rate of return process is unobservable at points in time, its time integral over successive observations is observable since it equals the increment of log-prices. Exact discretization delivers an ARIMA(1,1,1) model for log-prices with a fractional driving noise. Building on the resulting exact discretization formulae and covariance function, a new Markov Chain Monte Carlo (MCMC) scheme is proposed and we examine the properties of both the time and frequency domain likelihoods / posteriors through Monte Carlo. For the exact discrete model we adopt a general sampling interval of length h. This allow us to determine the optimal choice of h independent of the sample size. An empirical application using high frequency stock price data is presented showing the relevance of aggregation over time issues in modelling asset prices.

In this study, additive manufacturing of reinforced parts using metallic wire as both a reinforcement component and a shape memory stimulus through Fused Deposition Modeling (FDM) was investigated. A Shape Memory Polymer (SMP) restores its original shape and recovers it upon specific stimuli. This research employed chromium-nickel metal wire as a reinforcing component to enhance mechanical properties and introduce the capability for thermal stimulation of polylactic acid (PLA) via electrical current using the "in-situ impregnation" method within FDM process. Reinforced specimens were fabricated with wire with two diameters of 0.1 and 0.15 mm, along with two volume percentages of 5 and 10. Comprehensive evaluations encompassing mechanical (tensile and flexural) and thermal properties of the printed specimens were conducted. The outcomes revealed a significant enhancement in both tensile and flexural properties of the polymer matrix due to the embedding metallic wire, even under elevated temperatures during bending test. Furthermore, the thermal properties of the reinforced specimens were examined by subjecting them to various voltages, resulting in temperature ranging from 36.4 to 150.1°C. These findings highlight the ability to tailor a wide range of mechanical properties and shape recovery in the reinforced specimens by carefully selecting the wire volume fraction, voltage, and wire diameter, thus regulating the materials properties with specific application requirements.

Resistive random-access memory has emerged as a promising non-volatile memory technology, garnering substantial attention due to its potential for high operational performance, low power consumption, and scalability. Two-dimensional nanostructured materials play a pivotal role in RRAM devices, offering enhanced electrical properties and physical attributes that contribute to overall device improvement. In this study, self-rectifying switching behavior in RRAM devices is proposed based on molybdenum disulfide nanocomposites decorated with palladium on SiO2/Si substrates. The integration of Pd and MoS2 at the nanoscale effectively mitigates leakage currents decreasing from cross-talk in the RRAM array, eliminating the need for a separate selector device. The successful demonstration of the expected RRAM switching behavior follows the application of a Pd nanoparticle coating. The fabricated Pd-MoS2 synaptic device showed a high current ratio for forward/reverse current higher than 60 at a low resistance state and observed a memory on/off ratio of 103 performing stable resistance switching behavior.

The purported cognitive benefits associated with nicotine and its metabolites in the brain are a matter of debate. In this review, the impact of the pharmacologically active metabolite of a nicotine derivative produced by bacteria (6-hydroxy-L-nicotine) on memory, oxidative stress, and the activity of the cholinergic system in the brain was examined. A search in the PubMed, Science Direct, Web of Science, and Google Scholar databases, limiting entries to those no later than July 2023, was conducted. The search focused specifically on articles pertaining to nicotine metabolites, memory, oxidative stress, cholinergic system activity, as well as enzymes or pathways related to nicotine degradation in bacteria. The preliminary search resulted in 696 articles, and following the application of exclusion criteria, 185 articles were deemed eligible for inclusion. This review focuses on experimental studies supporting nicotine catabolism in bacteria, and the chemical and pharmacological activities of nicotine and its metabolite 6-hydroxy-L-nicotine.

The best form of prevention against human infection through bacteria, viruses and other parasites is ozone disinfection of wastewater and drinking water as a highly effective, well-known method. As a therapeutic measure, various preclinical studies showed promising results, which are being revisited and reconsidered in times of pandemics and led to interesting results in recent clinical trials and reports, as presented by the example of protective measures against covid-19 in particularly vulnerable clinical personnel. In patients with rheumatoid arthritis, repeated ozone treatments have led to new findings in the "immunomodulation" through ozone. The more effective immune response is discussed as the response of innate immune memory and opens interesting aspects for complementary treatment of autoimmune diseases.

Astragaloside IV (AIV) – triterpenoid saponin from the Astragalus mongholicus roots with the proved acetylcholinesterase (AChE)-inhibitory capability was used as the substance with the potential to attenuate memory impairment. Scopolamine (SCOP), antagonist of muscarinic cholinergic receptors and lipopolysaccharide (LPS), neuroinflammation inducer were used to impair memory processes in the passive avoidance (PA) test in mice. This memory impairment in the SCOP-treated mice was attenuated by the earlier intraperitoneal (ip) administration of AIV in the dose of 25 mg/kg. The reduction of memory impairment by LPS was not observed, therefore AIV does not reverse memory impairments through the anti-inflammatory mechanisms. All the studied doses of AIV did not affect basic locomotor activity of mice. As a result of the post-mortem analysis of mice body tissues, the largest content of AIV was determined in the kidneys, then in the spleen, liver and the smallest one in brain by mass spectrometry.

Long Covid is a term used for patients who have recovered from COVID-19 but exhibit persistent cognitive dysfunction, including mental confusion, difficulties in attention, impairment in executive functions and slow movements, among other common symptoms. A study was conducted with 65 patients who had a positive RT-PCR diagnosis and reported symptoms of cognitive impairment, such as memory loss and attention difficulties after recovery. The patients underwent neuropsychological evaluation and completed questionnaires on cognition, mood, and quality of life. During the cognitive screening, 71% of the patients showed alterations, with deficits in visual memory (69%), language (54%), visuospatial construction (49%), verbal episodic memory (37%), executive functions (36%), attentional abilities (34%), and premorbid intelligence (12%). It is important to highlight the need for treatments and further studies to understand the long-term side effects of this disease.

Shape Memory Polymer (SMP) actuators are smart materials that adapt and switch shape in response to environmental conditions, allowing controlled and dynamic building systems. The integrated SMP strip enabled the adaptive facade shading system to operate independently and with flexibility under certain thermoresponsive conditions to regulate building performance. This study aims to improve adaptive façade performance in a hot-humid climate by determining optimal thermal activation factors for the shape memory polymer. This was achieved by comprehensively examining and analysing the impact of various SMP activation parameters on energy efficiency, thermal comfort, and visual comfort. In addition, dynamic IES-VE building energy simulation was used to evaluate the thermal performance of the adaptable facade. The results were validated using a multicriteria approach to compare with the existing glass façade of a high-rise apartment. The results showed that the coactivation technique, which combines solar radiation and air temperature triggers, proved to be the most efficient strategy to improve the performance of the adaptive façade. This strategy minimised heat gain, lowered indoor temperatures, reduced glare, and enhanced daylight comfort, resulting in notable energy savings through reduced cooling consumption. The study concluded that the utilisation of SMP actuators with fine-tuning activation parameters significantly optimised adaptive façade performance, promoting functionality, efficiency, and sustainability in buildings.

Fluctuating stock prices make it difficult for investors to see investment opportunities. One tool that can help investors overcome this is forecasting techniques. Long Short-Term Memory (LSTM) is one of deep learning methods used in forecasting time series. The training and success of deep learning is strongly influenced by the selection of hyperparameters. This research uses a hybrid method between the Genetic Algorithm (GA) and LSTM to find a suitable model for predicting stock prices. GA is used in optimizing the architecture such as the number of epochs, window size, and the number of LSTM units in the hidden layer. Tuning optimizer is also carried out using several optimizers to achieve the best value. From method that has been applied, it shows that the method has a good level of accuracy with MAPE values below 10% in every optimizer used. The error rate generated is quite low, in case-1 with a minimum RMSE value of 93.03 and 94.40, & in case-2 with an RMSE value of 104.99 and 150.06 during training and testing. A fairly stable and small value is generated by setting it using the Adam Optimizer.

In this study, we demonstrate how the incorporation of appropriate feature engineering together with the selection of a Machine Learning (ML) algorithm that best suits the available dataset, leads to the development of a predictive model for transformation temperatures that can be applied to a wide range of shape memory alloys. We develop a gradient boosting ML surrogate model capable of predicting Martensite Start, Martensite Finish, Austenite Start, and Austenite Finish transformation temperatures with an average accuracy of more than 95% by explicitly taking care of potential distribution changes when modeling different alloy systems. We included heat treatment, rolling, extrusion processing parameters, and alloy system categorical features in the model input features to achieve more accurate and realistic results. In addition, using Shapley values, which are calculated based on the average marginal contribution of features to all possible coalitions, this study was able to gain insights into the governing features and their effect on predicted transformation temperatures, providing a unique opportunity to examine the critical parameters and features in martensite transformation temperatures.

This study examined the relationship among the three domains of executive function (EF; cognitive shifting, inhibitory control, and working memory) to test the applicability of the unity-diversity model in preschoolers using both behavioral and fNIRS approaches. Altogether 58 Chinese preschoolers (34 boys, 24 girls, Mage = 5.86 years, SD = 0.53, Age range = 4.83-6.67 years) were administered the Dimensional Card Change Sort (DCCS), go/no-go, and missing scan task. Their brain activations in the prefrontal cortex during the tasks were examined using fNIRS. First, the behavioral results indicated that the missing scan task scores (working memory) correlated with the DCCS (cognitive shifting) and go/no-go tasks (inhibitory control). But the latter two did not correlate with each other. Second, the fNIRS results demonstrated that the prefrontal activations during the working memory task correlated with those in the same regions during the cognitive shifting and inhibitory control tasks. Still, the latter two did not correlate. The behavioral and neuroimaging evidence jointly indicates that the unity-diversity model of EF does apply to Chinese preschoolers.

In a collaborative forecasting task, experts may have unequal authority levels. However, this has rarely been considered reasonably in the existing fuzzy collaborative forecasting methods. In addition, experts may not be willing to discriminate their authority levels. To address these issues, an auto-weighting fuzzy weighted intersection (FWI) fuzzy collaborative intelligence approach is proposed in this study. In the proposed auto-weighting FWI fuzzy collaborative intelligence approach, experts’ authority levels are automatically and reasonably assigned based on their past forecasting performances. Subsequently, the auto-weighting FWI mechanism is established to aggregate experts’ fuzzy forecasts. The theoretical properties of the auto-weighting FWI mechanism have been discussed and compared with those of the existing fuzzy aggregation operators. After applying the auto-weighting FWI fuzzy collaborative intelligence approach to a case of forecasting the yield of a DRAM product from the literature, its advantages over several existing methods were clearly illustrated.

Beer fermentation is typically monitored by periodic sampling and off-line analysis. In-line sensors would remove the need for time-consuming manual operation and provide real-time evaluation of the fermenting media. This work uses a low-cost ultrasonic sensor combined with machine learning to predict the alcohol concentration during beer fermentation. The highest accuracy model (R2=0.952, MAE=0.265, MSE=0.136) used a transmission-based ultrasonic sensing technique along with the measured temperature. However, the second most accurate model (R2=0.948, MAE=0.283, MSE=0.146) used a reflection-based technique without the temperature. Both the reflection-based technique and the omission of the temperature data are novel to this research and demonstrate the potential for a non-invasive sensor to monitor beer fermentation.

Shape memory alloys (SMAs) are increasingly used in the fields of aviation, automotive and biomedicine due to their unique properties. Nickel-Titanium (NiTi) alloy materials, which are one of the shape memory alloys, are among the most frequently used alloy materials. The shape memory and super elastic effects of NiTi alloys, high ductility and deformation hardening make it difficult to shape burr. An additional problem is the formation of a white layer during machining. In this study, surface milling operations were performed in dry cutting conditions with uncoated cutting tools with different nose radii. The processing parameters were determined based on the experience gained as a result of the preliminary tests. Tungsten carbide cutting tools with different nose radii (0.4mm and 0.8mm) were used for the milling operations. Milling was carried out at three different cutting speeds (20, 35, 50 m/min), feed rates (0.03, 0.07, 0.14 mm/tooth), and a constant axial cutting depth (0.7 mm). As a result of our experimental studies, the best tool life was found to be in 0.8 mm nose radius cutting tools at 20 m/min cutting speed and 0.03 mm/tooth feed rate (0.264 mm). The minimum average surface roughness was found after milling with 0.8 mm nose radius cutting tool at 20 m/min cutting speed and 0.03 mm/tooth feed rate (0.346 μm). It has been determined that increasing the cutting tool nose radius reduces both the flank wear over the cutting tool and the average surface roughness.