Miracle-dz/UniFAR-FTUs huggingface dataset:
Diffusion and functional MRI findings and their relationship to behaviour in postconcussion syndrome: a scoping review

Postconcussion syndrome (PCS) is a term attributed to the constellation of symptoms that fail to recover after a concussion. PCS is associated with a variety of symptoms such as headaches, concentration deficits, fatigue, depression and anxiety that have an enormous impact on patients’ lives. There is currently no diagnostic biomarker for PCS. There have been attempts at identifying structural and functional brain changes in patients with PCS, using diffusion tensor imaging (DTI) and functional MRI (fMRI), respectively, and relate them to specific PCS symptoms. In this scoping review, we appraised, synthesised and summarised all empirical studies that (1) investigated structural or functional brain changes in PCS using DTI or fMRI, respectively, and (2) assessed behavioural alterations in patients with PCS. We performed a literature search in MEDLINE (Ovid), Embase (Ovid) and PsycINFO (Ovid) for primary research articles published up to February 2020. We identified 8306 articles and included 45 articles that investigated the relationship between DTI and fMRI parameters and behavioural changes in patients with PCS: 20 diffusion, 20 fMRI studies and 5 papers with both modalities. Most frequently studied structures were the corpus callosum, superior longitudinal fasciculus in diffusion and the dorsolateral prefrontal cortex and default mode network in the fMRI literature. Although some white matter and fMRI changes were correlated with cognitive or neuropsychiatric symptoms, there were no consistent, converging findings on the relationship between neuroimaging abnormalities and behavioural changes which could be largely due to the complex and heterogeneous presentation of PCS. Furthermore, the heterogeneity of symptoms in PCS may preclude discovery of one biomarker for all patients. Further research should take advantage of multimodal neuroimaging to better understand the brain–behaviour relationship, with a focus on individual differences rather than on group comparisons.
Malaria, COVID-19 and angiotensin-converting enzyme 2: what does the available population data say?

The etiopathogenesis of COVID-19 and its differential geographic spread suggest some populations are apparently ‘less affected’ through many host-related factors that involve angiotensin-converting enzyme 2 (ACE2) protein, which is also the entry receptor for SARS-CoV-2. The role of ACE2 has been well studied in COVID-19 but not in the context of malaria and COVID-19. We have previously suggested how malaria might intersect with COVID-19 through ACE2 mutation and here we evaluate the currently available data that could provide a link between the two diseases. Based on the existing global and Indian data on malaria, COVID-19 and the suggested ACE2 mutation, the association could not be examined robustly, neither accepting nor refuting the suggested hypothesis. We strongly recommend targeted evaluation of this hypothesis through carefully designed robust molecular epidemiological studies.
The cerebellar anatomy of red junglefowl and white leghorn chickens: insights into the effects of domestication on the cerebellum

Domestication is the process by which wild organisms become adapted for human use. Many phenotypic changes are associated with animal domestication, including decreases in brain and brain region sizes. In contrast with this general pattern, the chicken has a larger cerebellum compared with the wild red junglefowl, but what neuroanatomical changes are responsible for this difference have yet to be investigated. Here, we quantified cell layer volumes, neuron numbers and neuron sizes in the cerebella of chickens and junglefowl. Chickens have larger, more folded cerebella with more and larger granule cells than junglefowl, but neuron numbers and cerebellar folding were proportional to cerebellum size. However, chickens do have relatively larger granule cell layer volumes and relatively larger granule cells than junglefowl. Thus, the chicken cerebellum can be considered a scaled-up version of the junglefowl cerebellum, but with enlarged granule cells. The combination of scaling neuron number and disproportionate enlargement of cell bodies partially supports a recent theory that domestication does not affect neuronal density within brain regions. Whether the neuroanatomical changes we observed are typical of domestication or not requires similar quantitative analyses in other domesticated species and across multiple brain regions.
Learning from Community-Based Natural Resource Management (CBNRM) in Ghana and Zambia: Lessons for Integrated Landscape Approaches

HIGHLIGHTS Inclusive, equitable multi-actor collaboration and sustainability are key to CBNRM. In practice, donors, government agencies, NGOs and community elites often control decision-making. Ongoing collaboration across actors and scales requires long-term support and engagement. Integrated Landscape Approaches (ILAs) are promising for improved natural resource management. Learning from CBNRM and documenting ILA processes is needed for adaptive management. SUMMARY Land use in much of sub-Saharan Africa is dominated by legislative frameworks based on a strong colonial legacy, focusing strongly on state control and minimal devolution of management responsibilities to local communities. However, attempts to reconcile conservation and socio-economic development by increasing stakeholder engagement in community-based natural resource management (CBNRM) have been undertaken since the late 1980s. Based on a review of published literature on historical land-use trajectories, the evolution of CBNRM, and key respondent interviews with NRM experts in Ghana and Zambia, this paper asks: What lessons can be learned from CBNRM to inform integrated landscape approaches for more equitable social and ecological outcomes? The paper discusses the positive characteristics and persistent challenges arising from CBNRM initiatives in both countries. The former being, improved rights and resource access, an established institutional structure at the local level, and a conservation approach tailored to the local context. The latter include the absence of multi-scale collaboration, inadequate inclusive and equitable local participation, and limited sustainability of CBNRM initiatives beyond short-term project funding timelines. The paper argues that integrated landscape approaches can address these challenges and improve natural resource management in Ghana and Zambia. We urge landscape practitioners to consider how the lessons learned from CBNRM are being addressed in practice, as they represent both challenges and opportunities for landscape approaches to improve natural resource management.
Diel Activity Patterns of Two Syntopic Range-Restricted Geckos Suggest Idiosyncratic Responses to Climate Change

Measures of activity patterns in relation to environmental conditions provide insights into ecologically driven requirements and climate preferences of species, particularly for ectotherms, due to the strong relationship between body temperature (Tb) and environmental temperatures. Lygodactylus incognitus (cryptic dwarf gecko) and Lygodactylus soutpansbergensis (Soutpansberg dwarf gecko) are range-restricted endemics to the Soutpansberg Mountains, South Africa, and have recently been shown to be potentially vulnerable to the effects of climate change. This prompted us to study the relationship between the thermoregulatory characteristics and environmental temperatures for these syntopic species. Active geckos (i.e. those outside of a refuge) and environmental variables were recorded during scan surveys across two seasons. Binomial logistic regressions were used to predict and explain activity based on presence/absence measures and environmental variables for each species. Of the variables measured, air temperature (Ta) was the main predictor of activity for both species. Cryptic dwarf geckos were active in cooler Ta than warmer temperatures in comparison to Soutpansberg dwarf geckos. Cryptic dwarf geckos are thus well adapted to temperate conditions. Soutpansberg dwarf geckos appear well adapted for warmer conditions, as they were more likely to be active at higher Ta. Our findings suggest that both species will alter their daily activity times in response to changing climate, but that the cryptic dwarf gecko is likely to be more negatively impacted than the Soutpansberg dwarf gecko, due to their affinity for cooler temperatures and avoidance of the hottest temperatures exhibited during the study period. Therefore, although these broadly sympatric, syntopic, range-restricted species are closely related and have similar life histories, they occupy different thermal niches and are likely to respond to climate change idiosyncratically. Our findings caution against the overuse of proxy species in predicting species geographic distribution changes in response to climate change.
Structure, interface stability and hot-spots identification for RBD(SARS-CoV-2):hACE2 complex formation

ABSTRACT The nature of intermolecular interactions between the SARS-CoV-2 receptor binding domain (RBD) and its receptor, human angiotensin-converting enzyme 2 (hACE2) has been investigated by Langevin simulations to provides clarity from a dynamic and energetic point of view. Hinge prediction and cross-correlation matrix analysis by elastic network models were applied to better understand the interface dynamics that promote the interdomain surface complementarity adjustment. Main results regarding dynamic aspects indicate that there is a large network of different types of interactions i.e. hydrogen bonding, salt bridges and numerous hydrophobic interactions stabilising the complex. With respect to the energetic aspects, we identified and evaluated the energy strength of the primary amino acids involved in the interaction that likely stabilise complex formation. Our results indicate that Tyr449, Leu455, Phe456, Ala475, Phe486, Gln493, Gly496, Gln498, Thr500, Asn501, Gly502, and Tyr505 form the primary interface between the SARS-CoV-2 RBD and hACE2.
Biopreservation of yogurt against fungal spoilage using cell-free supernatant of Lactiplantibacillus pentosus 22B and characterization of its antifungal compounds

ABSTRACT The use of lactic acid bacteria (LAB) as biopreservatives to control fungal spoilage in food is a promising strategy in terms of natural food preservation. In this study, 300 LAB were isolated from different sources and screened for antifungal activity in vitro against 9 spoilage fungi. Moreover, the most active strain Lactiplantibacillus pentosus 22B was utilized in yogurt as a biopreservative against fungal spoilage. Characterization of the antifungal compounds based on fungal response to concentrated extract after enzymatic treatments, GC-MS, and headspace GC-MS showed that L. pentosus 22B potentially produced a variety of active compounds including organic acids, peptidic compounds, fatty acids, volatile compounds, and hydrogen peroxide. The application of cell free-supernatant produced by L. pentosus 22B in yogurt showed its ability to prevent fungal growth during 22 days at 25°C. This LAB strain is a potential candidate for yogurt biopreservation based on the antifungal activity of L. pentosus in yogurt which has been experimentally confirmed for the first time.
Optimization of microwave-assisted extraction of bioactive compounds from pistachio (Pistacia vera L.) hull

ABSTRACT Phenolic compounds were extracted from pistachio hull using microwave-assisted solvent extraction (MASE). The effects of four parameters, microwave power, extraction time, solvent to sample ratio, and ethanol concentration were evaluated. The extraction conditions were optimized by response surface methodology to enhance the total phenolic content (TPC). Optimal conditions were found as 140 W microwave power, 4.5 min extraction time, 19:1 (v/w) solvent to sample ratio, and 56% ethanol concentration to get maximum TPC (62.24 mg GAE/g dry hull). Also, MASE was compared with conventional solvent extraction (CSE) and MASE gave higher TPC, yield, and antioxidant activity.
Consistency and representativeness of integrated water vapour from ground-based GPS observations and ERA-Interim reanalysis

Abstract. This study examines the consistency and representativeness differences of daily integrated water vapour (IWV) data from ERA-Interim reanalysis and GPS observations at 120 global sites over a 16-year period (1995–2010). Various comparison statistics are analysed as a function of geographic, topographic, and climatic features. A small (±1 kg m−2) bias is found in the reanalysis across latitudes (moist in northern and southern midlatitudes and dry in the tropics). The standard deviation of daily IWV differences is generally below 2 kg m−2 but peaks in the northern and southern storm-track regions. In general, the larger IWV differences are explained by increased representativeness errors, when GPS observations capture some small-scale variability that is not resolved by the reanalysis. A representativeness error statistic is proposed which measures the spatiotemporal variability in the vicinity of the GPS sites, based on reanalysis data at the four surrounding grid points. It allows to predict the standard deviation of daily IWV differences with a correlation of 0.73. In general, representativeness differences can be reduced by temporal averaging and spatial interpolation from the four surrounding grid points. A small number of outlying cases (15 sites) which do not follow the general tendencies are further examined. It is found that their special topographic and climatic features strongly enhance the representativeness errors (e.g. steep topography, coastlines, and strong seasonal cycle in monsoon regions). Discarding these sites significantly improves the global ERA-Interim and GPS comparison results. The selection of sites a priori, based on the representativeness error statistic, is able to detect 11 out of the 15 sites and improve the comparison results by 20 % to 30 %.
From suburbanization to reurbanization? Changing residential mobility flows of families with young children in the Prague Metropolitan Area

ABSTRACT Contemporary housing preferences and related behaviour are highly diverse due to the variety of lifestyle cultures in cities, dissimilarities in residents’ resources, and urban changes. In recent years, the Prague Metropolitan Area in Czechia has seen gradual changes in residential mobility patterns. While suburbanization remains the most significant type of residential change, other processes have emerged. The aim of the article is to examine changes in the residential mobility patterns of families with young children living in and moving between different residential zones in the Prague Metropolitan Area. Migration data relating to individuals are used to examine spatial and temporal shifts in mobility flows. Even though suburbs are still the main destination for families with young children, the authors identified a certain degree of diversification in residential behaviour. They conclude that this finding points to the emergence of reurbanization tendencies towards the housing estates and intensifying mobility within residential zones with housing that is similar in appearance.
Examining the sensory impressions, value perception, and behavioral responses of tourists: the case of floating markets in Thailand

ABSTRACT This study investigates the relationship between sensory impressions and perceived value in explaining the behavior of floating market tourists. It also explores whether the effects of sensory elements and perceived value on the behavioral responses of tourists differ among the three stages of destination development. Integrated generalized structured component analysis and multigroup analysis are performed to verify the conceptual model. The findings of this work enhance the understanding of the floating market, which is a popular tourist destination worldwide. Based on these findings, theoretical and practical implications are presented from the perspective of tourist sensory experience.
The impact of risks management in the success of JIT implementation: Structural equations modeling for relational analysis in the Moroccan industry

Abstract For more than 30 years, supply chain management adopts just-in-time (JIT) strategy. The adoption of JIT has reduced wastes and total costs; however it leads to complexity and risks. Thus, top management has to recognize and address critical risks in JIT implementation. This is the main objective of this study, which aims at investigate the activities related to risk management in JIT implementation and their relation with critical success factors (CSFs) or the key activities executed during JIT implementation and the benefits obtained. The research model was evaluated using the structural equations modeling (SEM) with the LISEREL approach. The results forthcoming from the study shows that risk treatment is one of the most important factors for the successful JIT implementation, and that other factors, such as good relationship with suppliers, management commitment, and management of human resources, depend upon it.
Fast‐Response, Stiffness‐Tunable Soft Actuator by Hybrid Multimaterial 3D Printing

Soft robots have the appealing advantages of being highly flexible and adaptive to complex environments. However, the low‐stiffness nature of the constituent materials makes soft robotic systems incompetent in tasks requiring relatively high load capacity. Despite recent attempts to develop stiffness‐tunable soft actuators by employing variable stiffness materials and structures, the reported stiffness‐tunable actuators generally suffer from limitations including slow responses, small deformations, and difficulties in fabrication with microfeatures. This work presents a paradigm to design and manufacture fast‐response, stiffness‐tunable (FRST) soft actuators via hybrid multimaterial 3D printing. The integration of a shape memory polymer layer into the fully printed actuator body enhances its stiffness by up to 120 times without sacrificing flexibility and adaptivity. The printed Joule‐heating circuit and fluidic cooling microchannel enable fast heating and cooling rates and allow the FRST actuator to complete a softening–stiffening cycle within 32 s. Numerical simulations are used to optimize the load capacity and thermal rates. The high load capacity and shape adaptivity of the FRST actuator are finally demonstrated by a robotic gripper with three FRST actuators that can grasp and lift objects with arbitrary shapes and various weights spanning from less than 10 g to up to 1.5 kg.
Hey Alexa, why do we use voice assistants? The driving factors of voice assistant technology use

ABSTRACT This study identified three factors to predict the use of the artificial intelligence communication devices known as voice assistants such as Amazon’s Alexa or Apple’s Siri: technological factors (usefulness and perceived ease of use), social influence factors (personal and societal norms), and risk factors (privacy concerns and perceived security). Considering these factors as significant antecedents, this study proposed an extended Technology Acceptance Model. To examine the proposed model, an online survey was conducted with 558 respondents. The findings indicate that perceived usefulness, personal norms, and perceived security have positive relationships with attitudes toward using voice assistants. Additionally, privacy concerns had a negative relationship with attitudes toward using voice assistants, which in turn has a positive relationship with the behavioral intention. Practical and theoretical implications are discussed.
How gay men discuss their bodies online

ABSTRACT Research shows that gay men are highly susceptible to media effects on body image. A considerable amount of attention has been dedicated to the traditional media content that might have a negative effect on the way gay men perceive their bodies. However, far less attention has been given to the potentially harmful body-related content gay men are exposed to on the Internet. The present study is the first systematic content analysis of body-related posts gay men create and are exposed to on non-dating online social platforms. We analyzed the textual and visual elements of gay men’s body-related posts (N = 600) across four social media platforms popular among gay men to examine what and how gay men disclose about their bodies.
A Preliminary Study on Environmental Sound Classification Leveraging Large-Scale Pretrained Model and Semi-Supervised Learning

With the widespread commercialization of smart devices, research on environmental sound classification has gained more and more attention in recent years. In this paper, we set out to make effective use of large-scale audio pretrained model and semi-supervised model training paradigm for environmental sound classification. To this end, an environmental sound classification method is first put forward, whose component model is built on top a large-scale audio pretrained model. Further, to simulate a low-resource sound classification setting where only limited supervised examples are made available, we instantiate the notion of transfer learning with a recently proposed training algorithm (namely, FixMatch) and a data augmentation method (namely, SpecAugment) to achieve the goal of semi-supervised model training. Experiments conducted on bench-mark dataset UrbanSound8K reveal that our classification method can lead to an accuracy improvement of 2.4% in relation to a current baseline method.
Integrated Semantic and Phonetic Post-correction for Chinese Speech Recognition

Due to the recent advances of natural language processing, several works have applied the pre-trained masked language model (MLM) of BERT to the post-correction of speech recognition. However, existing pre-trained models only consider the semantic correction while the phonetic features of words is neglected. The semantic-only post-correction will consequently decrease the performance since homophonic errors are fairly common in Chinese ASR. In this paper, we proposed a novel approach to collectively exploit the contextualized representation and the phonetic information between the error and its replacing candidates to alleviate the error rate of Chinese ASR. Our experiment results on real world speech recognition datasets showed that our proposed method has evidently lower CER than the baseline model, which utilized a pre-trained BERT MLM as the corrector.
Biosorption of Methylene Blue from Aqueous Solution Using Mixed Algae

A mixture of algae biomass (Chrysophyta, Cyanophyta, and Chlorophyte) has been investigated for its possible adsorption removal of cationic dyes (methylene blue, MB). Effect of pH (1-8), biosorbent dosage (0.2-2 g/100ml), agitated speed (100-300), particle size (1304-89μm), temperature (20-40˚C), initial dye concentration (20-300 mg/L), and sorption–desorption were investigated to assess the algal-dye sorption mechanism. Different pre-treatments, alkali, protonation, and CaCl2 have been experienced in order to enhance the adsorption capacity as well as the stability of the algal biomass. Equilibrium isotherm data were analyzed using Langmuir, Freundlich, and Temkin models. The maximum dye-sorption capacity was 26.65 mg/g at pH= 5, 250 rpm, 89μm, 25˚C, and 50 mg/L as initial concentration. Four kinetic models were tested, pseudo first order, pseudo second order, intra- particle diffusion and Elovich model. Taking into account the analysis of the (SSR and X2), the data were best fitted to Temkin isotherm model. The pseudo-second order with higher coefficient of determination fitted the data very well. Thermodynamic parameters (ΓG0, ΓH0, ΓS0, Ea and S*) at temperature ranges of 293–313 K demonstrated that biosorption is an endothermic, spontaneous reaction and higher solution temperature favors MB removal by adsorption onto algae biomass. Results show that adsorption- desorption process lasts for five cycle before losing its efficiency and the recovery efficiency increased up to 80.52%.