Miracle-dz/UniFAR-FTUs huggingface dataset:
Honey Dressing Intervention with Diabetic Foot Ulcer: Systematic Review

Diabetic foot ulcers are one of the complications of diabetes mellitus that are often suffered by patients with a history of diabetes mellitus in addition to complications in the form of retinopathy. The purpose of this study was to collect appropriate types of therapy for wound care in diabetic foot ulcer patients. This study uses a systematic review approach. Article search was limited to inclusion criteria and exclusion criteria. The inclusion criteria in this study were diabetic patients with diabetic foot ulcers. The conclusion in this study is that honey is very effective for wound healing in diabetic foot ulcer patients, although there are several methods that are quite effective besides honey, namely the Vacuum Closing package (negative pressure wound care). Honey has been shown to reduce wound size and heal wounds
Huntington’s disease: Pathophysiology and therapeutic intervention

Huntington's disease [HD] is a progressive neurodegenerative condition characterized by movement disorder, cognitive impairment, and behavioral symptoms. It is inherited as an autosomal-dominant trait and normally manifests in mid-adulthood. HD is common in India and parts of Central Asia, with a prevalence rate of 4–8 per 100 000 in most European populations. Juvenile onset affects around 5–10% of cases, with signs appearing before the age of 20. Patients may show more parkinsonian symptoms such as bradykinesia, dystonia, tremors and a cognitive deficit in place of chorea. There is no therapy that can completely stop the condition from progressing. There are medications that can help to regulate chorea, dystonia, mental, and psychiatric disturbances. The study covers the disease's pathophysiology, as well as plants and phytochemicals that have been shown to be beneficial.
Parameter identification of nonlinear delayed dynamical system in microbial fermentation based on biological robustness

In this paper, the nonlinear enzyme-catalytic kinetic system of batch and continuous fermentation in the process of glycerol bio-dissimilation is investigated. On the basis of both glycerol and 1,3-PD pass the cell membrane by active and passive diffusion under substrate-sufficient conditions, we consider the delay of concentration changes on both extracellular substances and intracellular substances. We establish a nonlinear delay dynamical system according to the batch and continuous fermentation of bio-dissimilation of glycerol to 1,3-propanediol(1,3-PD) and we propose an identification problem, in which the biological robustness is taken as a performance index, constrained with nonlinear delay dynamical system. An algorithm is constructed to solve the identification problem and the numerical result shows the values of time delays of glycerol, 3-HPA, 1,3-PD intracellular and extracellular substances. This work will be helpful for deeply understanding the metabolic mechanism of glycerol in batch and continuous fermentation.
Selected types of corrosion degradation of pipelines

Abstract The paper deals with corrosion degradation of gas pipeline. Pipelines play very important role as means transporting gas media over long distances from producers to end-users. Gas pipelines present a risk of potential corrosion degradation that can result in their failure. Corrosion on internal surfaces of steel pipes takes place in CO2, H2S, H2O and chloride environment. Degradation of steel results in loss of mechanical properties, reduction in thickness and ultimate perforation and failure. Corrosion is the electrochemical process that involves the fl ow of electrical currents on a micro or macro scale. For corroding steel, the anodic and the cathodic reactions produces the electrochemical cell. Corrosion protection of internal pipeline surface is based mainly on chemical composition of gas and the use of inhibitors. Corrosion protection of the external steel surface of the product line involves coatings and cathodic protection.
New Representation of Plant Hydraulics Improves the Estimates of Transpiration in Land Surface Model

Transpiration represents more than 30% of the global land–atmosphere water exchange but is highly uncertain. Plant hydraulics was ignored in traditional land surface modeling, but recently plant hydraulics has been found to play an essential role in transpiration simulation. A new physical-based representation of plant hydraulic schemes (PHS) was recently developed and implemented in the Common Land Model (CoLM). However, it is unclear to what extent PHS can reduce these uncertainties. Here, we evaluated the PHS against measurements obtained at 81 FLUXNET sites. The transpiration of each site was estimated using an empirical evapotranspiration partitioning approach. The metric scores defined by the International Land Model Benchmarking Project (ILAMB) were used to evaluate the model performance and compare it with that of the CoLM default scheme (soil moisture stress (SMS)). The bias score of transpiration in PHS was higher than SMS for most sites, and more significant improvements were found in semi-arid and arid sites where transpiration was limited by soil moisture. The hydraulic redistribution in PHS optimized the soil water supply and thus improved the transpiration estimates. In humid sites, no significant improvement in seasonal or interannual variability of transpiration was simulated by PHS, which can be explained by the insensitivity of transpiration demand coupled to the photosynthesis response to precipitation. In arid and semi-arid sites, seasonal or interannual variability of transpiration was better captured by PHS than SMS, which was interpreted by the improved drought sensitivity for transpiration. Arid land is widespread and is expected to expand due to climate change, thus there is an urgent need to couple PHS in land surface models.
Diabetes mellitus y COVID-19: fisiopatología y propuesta de tratamiento para el control glucémico en el tiempo de la pandemia

El coronavirus 2 del síndrome respiratorio agudo grave es el tercer betacoronavirus desde el año 2003 capaz de ocasionar una infección del tracto respiratorio inferior, llevando, en casos críticos, al síndrome de dificultad respiratoria aguda y la muerte. La edad avanzada, la hipertensión arterial y la diabetes mellitus son, entre otros, tres factores determinantes en los peores desenlaces clínicos. Múltiples mecanismos pueden explicar la mayor susceptibilidad de las personas diabéticas a las infecciones respiratorias. La hiperglucemia crónica altera tanto a la inmunidad humoral como al celular. Esta enfermedad predispone a la sobreexpresión de la proteína de la membrana celular que sirve como receptora del virus y a una respuesta inflamatoria exacerbada, aumentando el riesgo de una descompensación y de la aparición de crisis hiperglicémicas. Ante la ausencia de un tratamiento efectivo o de una vacuna, todos los esfuerzos deben hacerse para procurar un buen control metabólico de los pacientes con diabetes mellitus con y sin COVID-19. Por lo anterior, se plantean en este artículo de reflexión, diferentes propuestas para el tratamiento de la diabetes mellitus en la unidad de cuidados intensivos, sin descartar la forma ambulatoria, en donde la telemedicina y otras tecnologías permitirán acortar la distancia y mantener las medidas de aislamiento preventivo.
Classification of Tweets for Video Streaming Services’ Content Recommendation on Twitter

Streaming services were popular platforms often visited by internet users. However, the abundance of content can be confusing for its users, prompting them to look for a recommendation from other people. Some of the users looked for content to enjoy with the help of Twitter. However, there were irrelevant tweets shown in the results, showing sentences not related at all to the content in the streaming services platform. This study addressed the classification of relevant and irrelevant tweets for streaming services’ content recommendation using random forests and the Convolutional Neural Network (CNN). The result showed that the CNN performed better in the test set with higher accuracy of 94% but slower in running time compared to the random forest. There were indeed distinctive characteristics between the two categories of the tweets. Finally, based on the resulting classification, users could identify the right words to use and avoid while searching on Twitter.Keywords: text mining, streaming services, classification, random forest, CNN
GC-FID METHOD DEVELOPMENT AND METHOD VALIDATION OF EUGENOL IN CLOVE OIL EXTRACTED BY HYDRODISTILLATION

Eugenol is the essential component of many spice oils such as clove, cinnamon leaf, basil, nutmeg, etc. The determination of the authenticity of the essential oil is pivotal for estimating the purity of any essential oil. Hence, there is a high time to identify the marker compounds present in a particular essential oil. From ancient times, clove oil is known for many physiological properties. It is also widely used in dentistry and has potent antioxidant property. In this study, eugenol content in clove oil was evaluated by using GC FID. The ICH guideline was used to determine the suitability of the analytical method developed and validated.
Linear and Non-Linear Modelling of Nigerian Crude Oil Prices

To model Nigeria crude oil prices, this analysis compared univariate linear models to univariate nonlinear models. The data for this analysis was gathered from the Central Bank of Nigeria (CBN) Monthly Statistical Bulletin. The upward and downward movement in the series revealed by the time plot suggests that the series exhibit a regime-switching pattern: the cycle of expansion and contraction. At lag one, the Augmented Dickey-Fuller test was used to test for stationarity. For univariate linear ARIMA (p, d, q)) and univariate nonlinear MS-AR, seven models were estimated for the linear model and two for the non-linear model. The best model was chosen based on the criterion of least information criterion, AIC (2.006612), SC (2.156581), and the maximum log-likelihood of (-150.5480) for the crude oil prices were used to pick MS-AR (1) for the series. In analysing crude oil prices data, the MS-AR model proposed by Hamilton outperforms the linear autoregressive models proposed by BoxJenkins. The model was used to predict the series' values over a one-year cycle (12 months).
A cross-space cascading failure hazard assessment method considering betweenness centrality and power loss

: In order to accurately assess the hazard caused by cross-space cascading failure in the cyber-physical power system, we propose a quantitative assessment method. This method builds a comprehensive framework of assessment that takes into account the betweenness centrality of attack graph and the consequences of failure. The betweenness centrality of each node in the attack graph is used to characterize the frequency of failure. By calculating the number of all nodes on each attack path, the frequency of a certain fault is calculated. The power loss of physical node caused by each cross-space cascading failure is used to characterize the consequences of the fault, which is combined with the frequency of failure and the urgency of troubleshooting to calculate the hazard assessment value of the cross-space cascading failure. Finally, a variety of cross-space cascading failures are implemented in the simulation environment of local cyber-physical power system and their hazards are evaluated. The effectiveness of the proposed assessment method is verified.
Characterization of white matter branching in human cerebella: quantitative morphological assessment and fractal analysis of skeletonized MR images

Introduction: The aim of the present study was to investigate branching characteristics of the human cerebellar white matter by the means of findings obtained from the quantitative morphological assessment and fractal analysis of the skeletonized MR images of the human cerebellum. Methods: Thirty individuals with no apparent brain pathology (15 males and 15 females, ranging from 18 - 30 years of age) participated in this study. Their normal T2-weighted MR images of the cerebellar vermis (midsagittal plane) were examined. The skeletonizing procedure and subsequent quantitative morphological assessment of the acquired skeletonized MR images were performed. The following parameters were determined: the number of branches, the number of junctions, the amount of end-point voxels, junction voxels and slab voxels, the average and maximum branch lengths, the longest-shortest patch length, and the number of triple and quadruple points. Additionally, the individual branches of the obtained digital skeletons of the cerebellar white matter were examined and the following parameters were assessed: branch length variability, Euclidean distance, and branch length/Euclidean distance ratio. A fractal analysis was performed using the box counting method prior to and after the MR image skeletonizing procedure. The values of the fractal dimensions (FD) of both skeletonized and non-skeletonized MR images were calculated. Results: It was established that the cerebella, which had the maximum values of the FD, possessed a large number of small branches approximately equal in length and which were connected by numerous junctions, forming numerous endpoints. Those cerebella, which had higher values of the average branch length and greater branch length variability, showed lower values of the FD. The key characteristics of the digital skeleton that determined the values of the FD of the cerebellum and its skeletonized MR images were the number of branches and the number of junctions that had the strongest correlational relationships with the FD of the skeletonized MR images. We submitted a proposition to consider the number of branches and amount of junctions as a diagnostic criterion in the determination of normal values of the FD. Conclusions: The obtained data can be used as diagnostic criteria in assessment of the morphofunctional state of the cerebellum using magnetic resonance imaging (MRI) technique.
Human Intelligence and Network Neuroscience

Flexibility is central to human intelligence and is made possible by the brain’s remarkable capacity to reconfigure itself – to continually update prior knowledge on the basis of new information and to actively generate internal predictions that guide adaptive behavior and decision making. Rather than lying dormant until stimulated, contemporary research conceives of the brain as a dynamic and active inference generator that anticipates incoming sensory inputs, forming hypotheses about that world that can be tested against sensory signals that arrive in the brain (Clark, 2013; Friston, 2010). Plasticity is therefore critical for the emergence of human intelligence, providing a powerful mechanism for updating prior beliefs, generating dynamic predictions about the world, and adapting in response to ongoing changes in the environment (Barbey, 2018). This perspective provides a catalyst for contemporary research on human intelligence, breaking away from the classic view that general intelligence (g) originates from individual differences in a fixed set of cortical regions or a singular brain network (for reviews, see Haier, 2017; Posner & Barbey, 2020). Early studies investigating the neurobiology of g focused on the lateral prefrontal cortex (Barbey, Colom, & Grafman, 2013b; Duncan et al., 2000), motivating an influential theory based on the role of this region in cognitive control functions for intelligent behavior (Duncan & Owen, 2000). The later emergence of network-based theories reflected an effort to examine the neurobiology of intelligence through a wider lens, accounting for individual differences in g on the basis of broadly distributed networks. For example, the Parietal-Frontal Integration Theory (P-FIT) was the first to propose that “a discrete parieto-frontal network underlies intelligence” (Jung & Haier, 2007) and that g reflects the capacity of this network to evaluate and test hypotheses for problem-solving (see also Barbey et al., 2012). A central feature
Comparative biotolerance of water spinach, Ipomoea aquatica, to heavy metal pollution in the Agodi Reservoir and the Ogunpa River, Oyo State, Nigeria

The biotolerance of water spinach (Ipomoea aquatica) to heavy metals was investigated in the Agodi Reservoir and its supplying source, the Ogunpa River, to examine the impact of aquatic pollution. I. aquatica was collected monthly from the Ogunpa River and the Agodi Reservoir. Atomic absorption spectrophotometry was used to analyse the concentration of heavy metals in the samples. A box plot was used to evaluate the tolerance of the plants to heavy metals and ecological risk quotients (ERQ) were calculated to indicate the threat to human health and environment. The concentrations of cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni) and zinc (Zn) in the plants were below standard thresholds, but cadmium (Cd), iron (Fe), manganese (Mn) and lead (Pb) were present in higher than permissible levels. The ERQ of Cd in I. aquatica in the Ogunpa River was at an elevated ecological risk level in January (3.450), May (3.125), June (8.175), August (1.900) and September (2.025). The ERQ of Co, Cr, Cu and Ni in plants from both the reservoir and the river were less than one. The ERQ and biotolerance of heavy metals in this study indicated that I. aquatica is effective in binding heavy metals.
Academic Help-Seeking Attitudes, and Their Relationship with Emotional Variables

Academic help seeking is a self-regulatory strategy that is closely related to students’ school functioning and successful school outcomes. The aim of the present study is to gain greater insight into the associations between help-seeking behavior and attitudes (i.e., emotional costs, perception of benefits, threats and avoidance of academic help seeking), and socio-emotional factors (i.e., functional social support, satisfaction with life, happiness, academic and social self-concept, emotional loneliness and social network). Two hundred and thirty-two students from three public secondary schools (53.9% girls; mean age = 16.61, SD = 2.85) participated in this study by completing the assessment form during school hours. As expected, the results showed significant associations between attitudes toward academic help seeking and socioemotional factors except for (1) perceived emotional cost of academic help seeking and happiness, academic self-concept and social network, (2) threat of academic help seeking and satisfaction with life and social network and (3) avoidance of academic help seeking and social network, in which cases the correlations were not significant. Finally, (1) emotional loneliness was found to be a significant predictor of the perceived emotional cost of academic help seeking, (2) functional social support, academic self-concept, social self-concept and subjective evaluation of the social network were found to be significant predictors of the perceived benefits of academic help seeking, (3) emotional loneliness and academic self-concept were found to be significant predictors of both threat of academic help seeking and avoidance of academic help seeking. The results of this study suggest that psycho-emotional variables play an important role in academic help-seeking strategies and can affect students’ final behavior in help seeking.
Aplikasi Recovery Tidal Model dalam Pemberian Relaxation Therapy Pada Resiko Perilaku Kekerasan

Emotional problems are a symptom of violent behavior. Interaction of nerve activity between the hypothalamus, limbic structures (amygdala and hyppocampus), and the higher cortical centers which are psychophysiological events of emotion in the human system. The purpose of this case study is to see the application of Tidal Model recovery in mental health in the provision of relaxation therapy. The search method used is a case study, and literature review. The author selects the analyzed journals to find the effectiveness of relaxation therapy against the risk of violent behavior and a journal on recovery that links therapeutic communication between nurses and patients. In the discussion of this paper, the sub-theme of therapeutic relationship between nurses and patients is found and also the self-awareness of patients who are part of the Tidal Model. By implementing relaxation therapy with the Tidal Model approach, there is a reduction in signs and symptoms in patients. Recommendations for nurses are able to become more empathetic nurses in implementing therapy and can support and encourage patient awareness in carrying out therapies that will bring patients into recovery.
Morphohistometric analysis of the effects of Coriandrum sativum on cortical and cerebellar neurotoxicity

Objective: Natural compounds can act as metal chelators and oxygen free radical scavengers, which allows them to be used as bioactive antagonists to heavy metals neurotoxicity. The aim of the study to analyze the morphometric effects of Coriandrum sativum (C. sativum) on lead-induced neurotoxicity. Materials and Methods: Forty Sprague-Dawley albino rats were divided into four equal groups (ten in each group): control group; coriander group: received aqueous C. sativum extracts (600 mg/kg BW for 60 days orally); lead (Pb) group: received a daily dose of lead acetate (Pb) (10 mg/kg BW for 60 days orally); Pb+ coriandrum group: received: aqueous C. sativum extract (600 mg/kg BW) prior to 10 mg/kg BW of Pb. The following parameters malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) were measured. Layers thickness and nuclei density were analyzed. Results: Lead levels in blood and tissues were decreased significantly in the Pb group and those findings were corrected significantly (p=0.001) with C. sativum addition. Data exhibited an increase in oxidative stress marker MDA and a decrease in antioxidant enzymes activities (SOD, CAT, and GPx) significantly in the Pb group and those effects were reversed significantly (p=0.001) by C. sativum administration. The cerebellar cortex and all layers of the somatosensory cortex thickness and nuclei density were diminished significantly in the Pb group. The morphometrical measurements were corrected significantly (p=0.001) by C. sativum. Conclusion: From the findings of the current study, Pb caused noticeable structural and functional variations in the cerebellar cortex and somatosensory cortex. C. sativum corrected these parameters as it possesses chelating and antioxidant potentials.
In silico Analysis of Alkaloids for Therapeutic Use in Treatment of Alzheimer's Disease by Targeting Acetylcholinesterase Enzyme

Alzheimer’s is a progressive mental deterioration associated with the degeneration of the cognition activities and memory loss. It is considered to be a multifactorial disease. One of the causes of the Alzheimer’s disease is the low concentration of the neurotransmitter named acetylcholine (ACh) at the synaptic cleft. Thus, inhibitor of Acetylcholinesterase (AChE), an enzyme whose function is to degrade the acetylcholine, is proved to be a promising candidate to treat this disease. Among the inhibitors are the natural alkaloids that also have an inhibitory effect on the AChE. In this study we have focused on the simple derivates of beta carbolime (a group of alkaloids) and studied their interaction with AChE via rigid protein-ligand docking approach.