Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of different extraction solvents on the yield and enzyme inhibition (a-amylase, a-glucosidase, and lipase) activity of some vegetables

Abstract. Maser WH, Maiyah N, Nagarajan M, Kingwascharapong P, Senphan T, Ali AMM, Bavisetty SCB. 2023. Effect of different extraction solvents on the yield and enzyme inhibition (a-amylase, a-glucosidase, and lipase) activity of some vegetables. Biodiversitas 24: 3320-3331. The present study investigated the in vitro inhibition of a-amylase, a-glucosidase, and lipase, and antioxidant activities (DPPH, metal chelating, and FRAP) of Allium cepa L. , Apium graveolens L. , Coriandrum sativum L. , and Petroselinum crispum (Mill.) Fuss using solvent 80% ethanol, absolute ethanol, acetone, methanol, n-hexane, chloroform, and hot water. The total phenolic content (TPC) and the FTIR and GC-MS characterization spectra were compared with the activities. The TPC of 80% ethanol extract in A. graveolens L. was the highest among the extracts, with 23.78 mg GAE/g extract. The 80% ethanol extract exhibited the most potent antioxidant activity on DPPH radical scavenging (A. graveolens, 125.57 mg AEAC/g extract), metal chelating (C. sativum, 92.85 mg EECC/g extract), and FRAP activities (C. sativum, 46.98 mg AEAC/g extract). The 80% ethanol extract showed the highest anti-a-amylase (P. crispum, 30.61 mmol ACE/g extract) and anti-a-glucosidase (A. cepa, 595.28 mmol ACE/g extract) activities. In comparison, the absolute ethanol extract of C. sativum showed the highest anti-lipase activity (42.10% inhibition). According to the FTIR spectra, the 80% ethanol extract of the four green leafy vegetables is predicted to have several active compounds. GC-MS identified the compounds responsible for the activity. Studies on the recovery potential of active compounds as oral agents to treat diabetes mellitus with certain solvents are very useful in producing oral agents and functional foods to prevent diabetes mellitus.
Pressure Overload and Right Ventricular Failure: From Pathophysiology to Treatment

Right ventricular failure (RVF) is often caused by increased afterload and disrupted coupling between the right ventricle (RV) and the pulmonary arteries (PAs). After a phase of adaptive hypertrophy, pressure-overloaded RVs evolve towards maladaptive hypertrophy and finally ventricular dilatation, with reduced stroke volume and systemic congestion. In this article, we review the concept of RV-PA coupling, which depicts the interaction between RV contractility and afterload, as well as the invasive and non-invasive techniques for its assessment. The current principles of RVF management based on pathophysiology and underlying etiology are subsequently discussed. Treatment strategies remain a challenge and range from fluid management and afterload reduction in moderate RVF to vasopressor therapy, inotropic support and, occasionally, mechanical circulatory support in severe RVF.
Application of antimicrobial peptides in plant protection: making use of the overlooked merits

Pathogen infection is one of the major causes of yield loss in the crop field. The rapid increase of antimicrobial resistance in plant pathogens has urged researchers to develop both new pesticides and management strategies for plant protection. The antimicrobial peptides (AMPs) showed potential on eliminating plant pathogenic fungi and bacteria. Here, we first summarize several overlooked advantages and merits of AMPs, which includes the steep dose-response relations, fast killing ability, broad synergism, slow resistance selection. We then discuss the possible application of AMPs for plant protection with above merits, and highlight how AMPs can be incorporated into a more efficient integrated management system that both increases the crop yield and reduce resistance evolution of pathogens.
Lawton’s Instrumental Activities of Daily Living for Greek-Speaking Adults with Cognitive Impairment: A Psychometric Evaluation Study with Additional Receiver Operating Characteristic Curve Analysis

One of the components of a dementia diagnosis is the assessment of functional abilities. These abilities are measured via screeners, such as the Instrumental Activities of Daily Living (IADL) scale. The IADL scale is a valid tool that has been adapted in many languages. This study aimed to provide a cut-off point and validate the Greek version of the IADL scale in populations with cognitive impairment. IADL data were collected from 132 individuals: 24 PD patients, 24 Parkinson’s disease dementia (PDD) patients, and 24 AD patients. The remaining 60 participants were cognitive healthy adults (CHAs). The CHA group and the PD group served as the cognitively unimpaired group (CUG), while the PDD and AD groups served as the cognitively impaired group (CIG). Additionally, the MMSE, the AMTS, the Clock Drawing Test CDT, the Arizona Battery for Communication Disorders of Dementia (ABCD), the NPI, and the GDS-15 were administered to the participants. Statistically significant differences in the IADL scores were exhibited between all subgroups. The IADL scale showed high internal consistency (Cronbach’s alpha = 0.890). A threshold equal to 6.00 (AUC = 0.888, p < 0.001) was estimated between the CUG and the CIG. Significant positive correlations were observed between IADL and MMSE (r = 0.764, p < 0.001), IADL and AMTS (r = 0.724, p < 0.001), IADL and ABCD (r = 0.702, p < 0.001), and IADL and CDT (r = 0.627, p < 0.001) results. Given the obtained results, the IADL scale is a valid tool for clinical use with high reliability and sensitivity. Also, the IADL scale is a valuable instrument for screening functional abilities associated with cognitive impairment.
Elastic Chiral Waveguides with Gyro-Hinges

This article presents a novel chiral structure, consisting of Euler–Bernoulli beams connected to gyroscopic spinners.Anew type of boundary condition is introduced, which is referred to as a gyrohinge. In this system, flexural waves are coupled with rotational motion.Time-harmonic conditions are derived by assuming small nutation angles of the spinners. It is shown that the eigenfrequencies of a finite beam with gyro-hinges at one or both ends change dramatically with the moments of inertia and the spin and precession rates of the spinners. The formulation is then extended to elastic beams with periodically-spaced gyro-hinges, whose dispersion properties are investigated in detail. In particular, it is shown how stop-bands and standing modes are affected by the introduction of gyroscopic spinners at the junctions. It is also demonstrated that a periodic system composed of beams connected by gyro-hinges represents a good approximation of a gyrobeam, a theoretical structural element consisting of an elastic beam possessing a continuous distribution of stored angular momentum. The gyricity coefficient of a gyrobeam is then interpreted in terms of the physical parameters of the system of beams with gyroscopic spinners. This article opens a new perspective on the design and practical implementation of chiral mechanical systems.
ADVANCEMENT IN CHARACTERIZATION AND BIOLOGICAL ACTIVITIES OF CHITOSAN AND CHITOSAN OLIGOSACCHARIDES

Chitosan and its oligosaccharides exhibit numerous biochemical characteristics, which includes immune enhancing, antimicrobial and anti-viral properties. Chitosan and its products have drawn much attention of both food and pharmaceutical industry due to their peculiar physiochemical characteristics and effectiveness in cancer therapies. Current study describes the different physiological and chemical properties along with its usefulness in different biological processes. According to the novel studies, the focus of this study will be the anti-cancerous activities of COS. This study will summarize the whole mechanism related to the anti-cancerous functioning of COS along with the deep insight into the future perspectives of COS, especially at molecular level. Finally, future developments regarding the application of this biopolymer will be highlighted.
The impact of individualised funding on the wellbeing of mothers raising an autistic child in Aotearoa New Zealand

INTRODUCTION: How best to support the wellbeing of mothers raising autistic children is an emerging issue of importance due to the growth in autism diagnoses. While the move to individualised funding has been seen to promote autonomy for disabled people and their family to make decisions about services to meet their needs, it has also received criticisms, leading to inequitable processes and outcomes. The purpose of this research was to explore how individualised funding has impacted on mothers raising autistic children and their wellbeing. METHODS: A qualitative approach, combining semi-structured interviews and the theoretical underpinning of social constructionism, was used to interview seven mothers in 2020 to discuss their experiences of raising an autistic children and how individualised funding has impacted on them. Thematic analysis was used to analyse the data collected. FINDINGS: Key findings indicated that caring for an autistic child has an ongoing negative impact on mothers’ overall wellbeing and the individualised funding did not seem to ease the stresses of caring. CONCLUSION: Mothers raising an autistic child in Aotearoa New Zealand face complex funding systems, which are difficult to navigate. Individualisation of disability funding frameworks continues to create barriers and negatively impact the wellbeing of mothers. Wellbeing requires the funding support to see the family as a unit of care instead of the individualisation of a child’s needs. Results of this study urge practitioners and policymakers to support parents raising an autistic child in a more flexible and holistic way to meet the unique circumstances of a family.
EARLY ONLINE RELEASE

10 This paper reports the development of a very-short-range nowcast system, 11 VIL Nowcast, which aims to provide precise forecasts of imminent rain12 fall, and in particular, heavy and localized events. The system is based on 13 the vertically integrated liquid water content (VIL), which is estimated from 14 three-dimensional radar observations as well as the 1-minute-resolution rain15 fall map obtained from the X-band polarimetric (multi-parameter) RAdar 16 Information Network (XRAIN), to predict rainfall amounts over 10 minutes 17 periods that extend to 10–60 minutes into the future. The spatial resolu18 tion of VIL Nowcast was 500 m, and nowcasts were produced at a temporal 19 resolution of 5 minutes. Three precipitation events, of which two were iso20 lated storms and one was a synoptic storm, were used as case studies to 21 verify the model. The performance of VIL Nowcast was evaluated against 22 the XRAIN radar rainfall data and an existing rainfall-rate nowcast system 23 using the same advection scheme. The scope of the evaluation was limited 24 mainly to the first prediction for 10 minutes ahead. It was found that VIL 25 Nowcast showed a small, statistically significant improvement over the en26 tire precipitation event, although its skill decreased at longer lead times and 27 at higher thresholds. The key findings of this study are: (1) VIL Nowcast 28 appears capable of generating skillful forecasts at short lead times, even for 29 very localized heavy rainfall; (2) VIL Nowcast can reduce the time lag in 30
Physical Layer Security for NOMA Systems: Requirements, Issues, and Recommendations

Nonorthogonal multiple access (NOMA) has been viewed as a potential candidate for the upcoming generation of wireless communication systems. Comparing to traditional orthogonal multiple access (OMA), multiplexing users in the same time-frequency resource block can increase the number of served users and improve the efficiency of the systems in terms of spectral efficiency. Nevertheless, from a security viewpoint, when multiple users are utilizing the same time-frequency resource, there may be concerns regarding keeping information confidential. In this context, physical layer security (PLS) has been introduced as a supplement of protection to conventional encryption techniques by making use of the random nature of wireless transmission media for ensuring communication secrecy. The recent years have seen significant interests in PLS being applied to NOMA networks. Numerous scenarios have been investigated to assess the security of NOMA systems, including when active and passive eavesdroppers are present, as well as when these systems, are combined with relay and reconfigurable intelligent surfaces (RISs). Additionally, the security of the ambient backscatter (AmB)-NOMA systems are other issues that have lately drawn a lot of attention. In this article, a thorough analysis of the PLS-assisted NOMA systems research state-of-the-art is presented. In this regard, we begin by outlining the foundations of NOMA and PLS, respectively. Following that, we discuss the PLS performances for NOMA systems in four categories depending on the type of the eavesdropper, the existence of relay, RIS, and AmB systems in different conditions. Finally, a thorough explanation of the most recent PLS-assisted NOMA systems is given.
Diagnosing seasonal forecast skill of the Indian Ocean Dipole mode using model-analogs

A retrospective tropical Indian Ocean Dipole mode (IOD) hindcast for 1958–2014 was conducted using 20 models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), with a model-based analog forecast (MAF) method. In the MAF approach, forecast ensembles are extracted from preexisting model simulations by finding the states that initially best match an observed anomaly and tracking their subsequent evolution, with no additional model integrations. By optimizing the key factors in the MAF method, we suggest that the optimal do main for the analog criteria should be concentrated in the tropical Indian Ocean region for IOD predictions. Including external forcing trends improves the skills of the east and west poles of the IOD, but not the IOD prediction itself. The MAF IOD prediction showed comparable skills to the assimilation-initialized hindcast, with skillful predictions corresponding to a 4- and 3-month lead respectively. The IOD forecast skills had significant decadal variations during the 55-year period, with low skills after the early 2000s and before 1985 and high skills during 1985–2000. This work offers a computational efficiency and practical approach for seasonal prediction of the tropical Indian Ocean sea surface temperature.
Three-dimensional structure and functional studies of neopullulanase from Thermus brockianus

The structural guided-rational design has been suggested to meet the demand for pullulanase in starch industries. Neopullulanase (EC 3.2.1.135), a pullulan hydrolase type I belonging to the alpha-amylase family that hydrolysis α -1,4-glucosidic bonds in pullulan to produce panose is one such enzyme that can be manipulated. Therefore, this study aimed at modeling three 3- dimensional structures of neopullulanase from Thermus brockianus, a thermophilic bacteria belonging to the thermus genus. The multiple sequence alignment was carried out with Clustal Omega while the domain and 3D structure of this enzyme was predicted with Pfam and four different modeling servers. Model validation was done using SAVES 06 based on the Ramachandran plot and VERIFY3D analysis. YASARA was employed to minimize the energy of the model. PyMOL software was employed to visualize and superimpose the model with the template. The conserved residues and alpha-amylase domain were identified in this enzyme. The RaptorX model was found to be the best with 93.1% residues in the most favoured region based on the Ramachandran plot. The model energy was reduced to -281707.5 kJ/mol with 95.03% of the residues having an average score of 3D-1D score >= 0.2 in the VERIFY3D analysis. TIM barrel active site fold and the three important catalytic residues; Asp329, Glu360 and Asp431 were also identified. This structure prediction will be helpful in the improvement of neopullulanase for large-scale industrial use
Eigendecomposition-Free Sampling Set Selection for Graph Signals

This paper addresses the problem of selecting an optimal sampling set for signals on graphs. The proposed sampling set selection (SSS) is based on a localization operator that can consider both vertex domain and spectral domain localizations. We clarify the relationships among the proposed method, sensor position selection methods in machine learning, and existing SSS methods based on graph frequency. In contrast to the alternative graph signal processing-based approaches, the proposed method does not need to compute the eigendecomposition of a variation operator, while still considering (graph) frequency information. We evaluate the performance of our approach through comparisons of prediction errors and execution time.
Subsonic Frictional Cavitating Penetration of a Thin Rigid Body Into an Elastic Medium

Two model problems of plane elasticity on subsonic steady-state motion of a thin rigid body in an elastic medium are analyzed. Both models concern a finite body symmetric with respect to the plane of motion and assume that the body contacts with the surrounding medium according to the Coulomb friction law. The body, while moves, leaves a trailing semi-infinite cracklike cavity moving at the body speed. The first model also assumes that ahead of the body a finite crack-like cavity is formed, and it is moving at the same speed. The second model does not admit the existence of this finite cavity. Both problems reduce to two sequently solved Riemann–Hilbert problems with piece-wise constant coefficients. Analysis of the solution to these problems obtained by quadratures reveals that the normal and tangential traction components and the normal velocity are continuous for any point of separation of the medium from the body. A criterion for the separation point based on the analysis of the sign of the normal traction component is proposed. Numerical results for the length of the fore crack (the first model), the normal traction and the resistance force for some ogive-nose penetrators are reported.
An Efficient Network for Predicting Time-Varying Distributions

While deep neural networks have achieved groundbreaking prediction results in many tasks, there is a class of data where existing architectures are not optimal -- sequences of probability distributions. Performing forward prediction on sequences of distributions has many important applications. However, there are two main challenges in designing a network model for this task. First, neural networks are unable to encode distributions compactly as each node encodes just a real value. A recent work of Distribution Regression Network (DRN) solved this problem with a novel network that encodes an entire distribution in a single node, resulting in improved accuracies while using much fewer parameters than neural networks. However, despite its compact distribution representation, DRN does not address the second challenge, which is the need to model time dependencies in a sequence of distributions. In this paper, we propose our Recurrent Distribution Regression Network (RDRN) which adopts a recurrent architecture for DRN. The combination of compact distribution representation and shared weights architecture across time steps makes RDRN suitable for modeling the time dependencies in a distribution sequence. Compared to neural networks and DRN, RDRN achieves the best prediction performance while keeping the network compact.
Methamphetamine enhances neural activation during anticipation of loss in the monetary incentive delay task

Abstract Stimulants like methamphetamine (MA) affect motivated behaviors via actions on circuits mediating mood, attention, and reward. Few studies examined the effects of single doses of stimulants on reward circuits during anticipation and receipt of rewards and losses. Here, we examined the effects of MA (20 mg) or placebo in a within-subject, double-blind study with healthy adults (n = 43). During 2 fMRI sessions, participants completed the monetary incentive delay task. Primary outcome measures were BOLD activation in selected regions of interest during anticipation and receipt of monetary rewards and losses. Secondary analyses included behavioral measures, whole brain analysis, and arterial spin labeling. MA produced its expected behavioral effects and increased neural activation in the ventral striatum and anterior insula during anticipation of monetary loss versus non-loss. MA did not affect activation during anticipation of gains, or during receipt of wins or losses. MA significantly reduced cerebral blood flow in the striatum and insula. The present finding that a stimulant enhances the responses of striatal and insular regions to upcoming loss suggests that this system may be sensitive to the salience of upcoming events. The finding adds to a complex body of evidence regarding the effects of stimulant drugs on neural processes during motivated behaviors.
Design and Fabrication of an Ag Ultrathin Layer-Based Transparent Band Tunable Conductor and Its Thermal Stability

Transparent conductors (TC) have been widely applied in a wide range of optoelectronic devices. Nevertheless, different transparent spectral bands are always needed for particular applications. In this work, indium tin oxide (ITO)-free TCs with tunable transparent bands based on the film structure of TiO2/Ag/AZO (Al-doped ZnO) were designed by the transfer matrix method and deposited by magnetron sputtering. The transparent spectra and figure-of-merit (FOM) were effectively adjusted by precisely controlling the Ag layer’s thickness. The fabricated as-deposited samples exhibited an average optical transmittance larger than 88.3% (400–700 nm), a sheet resistance lower than 7.7 Ω. sq−1, a low surface roughness of about 1.4 nm, and mechanical stability upon 1000 bending cycles. Moreover, the samples were able to hold optical and electrical properties after annealing at 300 °C for 60 min, but failed at 400 °C even for 30 min.
On globally stable adaptive control providing l 1 tracking performance for linear discrete-time systems

ABSTRACT Existing adaptive control algorithms at best guarantee that the tracking error is a l 2 sequence. This paper presents globally stable adaptive control algorithms for linear discrete-time systems providing l 1 tracking performance. Two algorithms with different degree of complexity are proposed, one for the case of known control directions, and a separate algorithm for the case of unknown control directions. It is demonstrated that in both cases the tracking error is l 1 sequence, while the input and output signals are uniformly bounded.
Heat Transfer Analysis without and with Forward Facing Spike Attached to a Blunt Body at High Speed Flow

The present chapter deals with heat transfer analysis around unspiked and spiked bodies at high speeds. A spike attached to a blunt-nosed body drastically alters its flowfield and influences the aerodynamic heating in a high speed flow. The effect of spike length, shape and spike-nose configuration is numerically studied at zero angle of incidence. The numerical analysis describes overall flowfield features over without and with forward facing spike attached to a blunt body at high speed flow. The shock stand-off distance, sonic line, stagnation point velocity gradient and stagnation point heat flux are analyzed and compared with different aerodisk configurations. It is found that the hemispherical aerodisk experiences high wall heat flux as compared to the flat-faced aerodisk. Numerical and experimental studies reveal that the wall heat flux levels are decreased in the presence of the spikes and aerospike as compared to without attached spiked to the blunt-nose basic configuration.