Miracle-dz/UniFAR-FTUs huggingface dataset:
The “Counseling+” Roles of the Speech-Language Pathologist Serving Older Adults With Mild Cognitive Impairment and Dementia From Alzheimer’s Disease

Purpose: Persons with dementia and mild cognitive impairment (MCI) are major consumers of services provided by speech-language pathologists (SLPs). These services include not only direct assessment and treatment of communication and swallowing but also counseling, collaboration, prevention, and wellness. These “counseling+” activities can be especially challenging for SLPs to deliver because of the lack of evidence, as well as the complex nature of Alzheimer’s disease (AD) and other conditions that cause MCI and dementia. Method: This tutorial is written by a speech-language pathologist, a neuropsychologist, and a geriatric psychiatrist to provide education, resources, and recommendations for SLPs delivering counseling+ activities to patients with MCI and dementia from AD and related disorders. Results and Conclusions: We describe counseling+ activities across the continuum of care ranging from educating and conducting cognitive screenings with adults experiencing age-related cognitive decline to supporting end-of-life wishes. Because of their expertise in communication, SLPs can provide an array of important leading and supporting services to patients, their family, and other health care professionals on the care team, such as providing patients with appropriate feedback following a cognitive screening and helping caregivers identify the communicative intent of a responsive behavior. The demand for SLP services for patients with MCI and dementia will grow significantly over the next few decades, necessitating more systematic research and clinical evidence in this area.
An efficient mechanism to detect and mitigate an ARP spoofing attack in software-defined networks

The work focuses on software-deﬁned network security, as it was always one of these foremost critical concerns due to the centralized nature in SDN architecture where many serious attacks in traditional networks still appear in SDN networks such as ARP spooﬁng attack despite many existing security algorithms, methods and systems. In this work, we proposed a new approach to secure SDN from an ARP poisoning attack. The new solution extends the controller with a new module that uses a new algorithm to detect and mitigate the ARP spooﬁng attacks according to three states of each host in the network. The new mechanism involves the DHCP and manual assignment of IP addresses using three classes to classify the hosts according to their situations in the network. The CHT helps to set the host in an intermediate state between verifying and banning and detect the attack according to the next step of the host. The proposed mechanism was tested successfully in a simulated environment using Mininet and POX controller. The solution was effectively able to accomplish the objective for which it was built, with a limited overhead on the network. This proposed solution neither has an extra overload in the network, nor requires any changes in the infrastructure or additional hardware to install. According to the experiment results of this solution, the average time to detect the ARP spooﬁng attack is about 11 ms, with minor overhead on the controller CPU.
Feasibility of Polyvinyl Alcohol-Treated Soil in a Mud State as the Anti-Weathering Material for Earthen Sites

ABSTRACT Earthen sites have important historical, cultural, artistic, social, and scientific values. However, they have been seriously destroyed by weathering. The methods of in situ replacement and sacrificial layer were previously presented to protect the surface of the earthen sites. This work presents the feasibility of the polyvinyl alcohol (PVA)-treated soil in a mud state as the anti-weathering material for these two methods. The desiccation cracking behaviour of soil was the main concern, and the surface peeling, hardness, and colour difference were used as the auxiliary evaluation criteria. The results showed that the PVA solution with a high degree of alcoholysis effectively inhibited soil cracking, but cannot eliminate all cracks even if the content reached 1%. The cracks of samples with the PVA mainly developed when the water content exceeded water content corresponding to air-entry value. Filamentous (or meshy) connections and cementation between particles were the main reason to inhibit the development of the cracks. The obvious advantages of the PVA in the decohesion index, hardness, colour difference, and so on cannot be also ignored. Based on these evaluation indicators, a PVA content of 0.8% may be the best choice for anti-weathering of earthen sites.
Mapping Microbiome Signatures Associated With Antibiotic Usage On A Swine Production Farm Using Amplicon And Shotgun Data

Background: High antimicrobial usage in swine production has the potential to create reservoirs of antimicrobial resistance (AMR) genes which are transferable to human pathogens via mobile genetic elements. Understanding microbial community responses to antibiotic use is central to unravelling transfer of such resistance genes. Our previous investigation revealed a scenario of optimal antibiotic activity associated with saturation of AMR genes on this farm. Here, we use amplicon and shotgun sequence data to investigate the microbiome signatures that underwrite such a phenomenon.Results: We generated 1.24 and 576 million high quality 16S rRNA gene amplicon and shotgun sequences from 24 porcine faecal samples, respectively. The ratio of taxa detection at genus level between the two methods was 1:24. Using shotgun sequence data, 235 unique AMR genes, 122 modes of action and 17 antibiotic classes were identified using the MEGARes AMR database. Antibiotic usage in growing pigs was significantly associated with microbial and AMR resistome structural and compositional changes detectable two weeks after antibiotic initiation. These were characterised by a down regulation of MDR efflux pumps and an up regulation of macrolide-specific efflux pumps in the growing pigs (treated-group) linked to lower abundance of Verrucomicrobiaeceae. In the sows (non-treated group), a potentially undetected infection, was characterised by a high abundance of pathogenic viral sequences, microbial structural changes i.e. family Alcaligenaceae, and an up regulation of beta-lactamases, including MDR efflux pumps. We assembled 682 near complete bacterial genomes revealing that a large proportion of the resistome is carried by Firmicutes and Proteobacteria, specifically multi-class gene carriage by Clostridium species and Escherichia coli, which occurred exclusively in the treatment group.Conclusion: Microbiome signatures i.e. microbial structure, composition and resistome carriage associated with antibiotic-use can be cost effectively screened with amplicon sequencing but their granularity unravelled using shotgun metagenomic data.
Dynamic Optimization Self-adaptive AI Controller for a Four-wheel Independent Drive Electric Rover

In this paper, a dynamic optimization self-adaptive controller for a four-wheel independent drive electric rover has been investigated to enhance the dynamic stability. The proposed self-adaptive AI controller is based on dynamic Fuzzy Logic (FL) control mechanism. The dynamic self-adaptive properties have been integrated into the proposed FL controller through a dynamically tuned Particle Swarm Optimization (PSO) mechanism. Nevertheless, the dynamic FL controller and the dynamic PSO mechanism has been synchronized together for every sampling instance k to obtain the optimum performance of the electric rover. In this electric rover, all the four wheels have a fixed orientation and each wheel powered by a 250-Watt Brushless Direct Current (BLDC) motor through separate gear ratio mechanisms to obtain the desired torque and angular velocity. Therefore, the steering mechanism was achieved in this rover through the proposed AI controller, which was based on the differential speed mechanism. However, this paper presents the control methodology and obtained test results related to straight road tests under different slippery road conditions. The rover test results show that on different slippery road conditions the proposed PSO based FL controller has maintained the wheel slip ratio of all the four wheels which was less than 0.35 approximately. Here, the translational speed has been limited to 40 km/hr approximately within its recorded top speed of 90 km/hr while maintaining the desired fix orientation.
Characterization and Microstructural Evolution of WC-Co Cemented Carbides

Two types of cemented carbides have been elaborated from three mixtures of WC and Co powders containing 3, 5 and 6% of cobalt mass. Three samples of these mixtures have been obtained by liquid phase sintering and three others of the same composition have been sintered then densified by hot isostatic pressing (HIP). Observations by scanning electronic microscope have allowed to note that the samples elaborated by sintering followed by an HIP densification have a more homogeneous structure than that observed in the sintered samples. Under the compression, the WC grains flattens and interlock more easily from one another which gives a uniform surface appearance. Energy dispersion analysis shows that these samples contain a very small voluminal fraction of graphite and residual porosities, these are more pronounced in sintered samples, especially in the case of alloys with a low Co content (3 and 5%). X rays diffraction analysis allowed to show clearly the existence of cobalt type carbide in the sintered samples. Measurement of the closed porosity allows to observe that the sintering process followed by densification by HIP leads to the elaboration of alloys with a low rate of closed porosity. Microhardness of these samples have improved hardnesses.
Corn shoot and grain nutrient uptake affected by silicon application combined with Azospirillum brasilense inoculation and nitrogen rates

Abstract This study was developed to investigate if Ca and Mg silicate application as Si source combined with inoculation with Azospirillum brasilense and N rates can affect corn nutrient uptake. The study was set up in a Rhodic Hapludox under no-till system, located in Selvíria, state of Mato Grosso do Sul, Brazil. Treatments included: (i) two seed inoculation (with and without A. brasilense); (ii) two soil amendment sources (Ca and Mg silicate as Si source and dolomitic limestone); and (iii) five N application rates applied as side-dress (0 to 200 kg ha−1). Increasing N rates positively influenced corn nutrition with increased nutrient and Si uptake in shoot and grain. The average nutrient uptake in descending order was K > N > Ca > Si > Mg > S > P >Fe > Mn > Zn > Cu > B for shoot and N > K > P > S > Mg > Ca > Si> Fe > Zn > Mn > B > Cu for grain. Calcium and Mg silicate application positively influenced corn nutrition with greater shoot P, K, Ca, S, and B uptake and grain Ca uptake. Inoculation with A. brasilense was found to increase nutrient uptake with greater shoot N, K, Ca, B, and Si and grain Cu uptake. Grain N and S increased by 22.5 and 26.8% when plants were inoculated and 200 kg N ha−1 was applied and grain Zn increased by 88.6, 65.7, and 99% when plants were inoculated and 50, 150, and 200 kg N ha−1 were applied, respectively. Therefore, studies conducted under tropical conditions are needed to better understand the role of Si combined with PGPB inoculation under different N management and their effects on plant nutrition and cereal development aiming at improving nutrient replenishment.
Socioeconomic and demographic predictors for adoption of new sugarcane varieties in Nandi County, Kenya

Despite there being high demand for sugarcane products globally, low yielding varieties in Kenya persist. A study was conducted in Nandi, Kenya to assess age, level of education, gender, level of awareness, price of produce and cost of changing to new varieties, perception of risks, planting materials and scale of farm operations as predictors of adoption for new sugarcane varieties. Purposive and multistage sampling techniques were used to select participants in the study. A sample of 198 farmers participated in the ex-post-facto survey study. Data was collected using questionnaires and analyzed using cross tabulations and logistic regression. All the variables except gender, price and costs showed significant (p < 0.05) relationship with adoption. A prediction model with the six explanatory variables was a well-fitting model, could correctly classify 87.4% of the outcome and explains 60.4% of the variation in adoption. It is concluded that farmers’ age, education, awareness, perception of risks and uncertainties about new varieties, availability of planting materials and scale of operation have significant association with and are significant predictors of adoption. It is recommended that for improved adoption, stakeholders consider the factors in their intervention plans. Further research on their effect on sugarcane productivity is recommended. Key words: Socio-economic, demographic, predictors, adoption, new sugarcane varieties, Nandi, Kenya.
An Automated System for Measuring In Situ K–Ar Ages

A completely automated system for measuring in situ K–Ar ages using laser ablation for argon extraction and potassium measurement, and mass spectrometry for argon determination is described. The system consists of a laser system, an optical spectrometer, a vacuum line, a noble gas mass spectrometer and control software. The automated prototype was designed with ease of use in mind, specifically planned for dating many samples at low cost and reasonable precision. This instrumentation can perform one hundred K–Ar analyses every 24 h with the current setup, including blanks, reference materials and unknowns. Measurement results for the reference materials HDB‐1 biotite, GL‐O glauconite, LP‐6 biotite, Mica‐Mg phlogopite, Alder Creek sanidine and two tektites (moldavite and indochinite) are presented. It is shown that very different sample matrices require specific calibrations. Uncomplicated sample preparation, fast analytical times and uncertainties typically below 5% (1 standard deviation), depending on the age and potassium content, are the hallmarks of the system, which is suitable for many exploratory geology applications (e.g. geological mapping, mineral provenance and dating of drill cores).
A Pipeline for Manual Annotations of Risk Factor Mentions in the COVID-19 Open Research Dataset

We here demonstrate how a set of tools that are being maintained and further developed within the Sprakbanken Sam and SWE-CLARIN infrastructures can be employed for creating manually labelled training data in a low-resource setting. As example text, we used the “COVID-19 Open Research Dataset”, and created manually annotated training data for its associated Kaggle task, “What do we know about COVID-19 risk factors? ”. We first used our topic modelling tool to i) select a text set for manual annotation, ii) classify the texts into preliminary classification categories, and iii) analyse the texts in search for potential refinements of the annotation categories. We then annotated the text set on a more granular level by labelling the token sequences that indicated the existence of the refined categories in the text. Finally, we used the granularly annotated text set as a seed set, and applied our active learning tool for actively selecting additional texts for annotation. For the token-sequence annotations, we used our text annotation tool, which includes support for incorporating automatic pre-annotations.
Laplacian large margin distribution machine for semi-supervised classification

Abstract Semi-Supervised Learning (SSL) has attracted much attention in the field of machine learning and data mining. As an extension of Support Vector Machine (SVM), the Semi-Supervised Support Vector Machine (S3VM) was proposed for SSL. Recent studies have disclosed that optimising the margin distribution is more crucial than maximising the minimum margin in generating a better classification. However, the existing S3VM models still follow the idea of maximising the minimum margin. Therefore, this paper proposes a novel Laplacian Large margin Distribution Machine (LapLDM) for SSL to enhance the classification performance. This method can optimise the margin distribution by maximising the first-order (margin mean) and minimising the second-order (margin variance) statistics of margins, and exploit the geometry information of marginal distribution embedded in the unlabelled data through the Laplacian regularizer. Then this paper develops a Preconditioned Conjugate Gradient (PCG) algorithm to solve the nonlinear LapLDM model on those regular-scaled data sets and a Stochastic Gradient Descent with Variance Reduction (SVRG) algorithm to solve the linear LapLDM model on those large-scaled data sets. These algorithms can accelerate the implementing efficiencies of proposed models and make them available for those large-scaled problems. Finally, the numerical results on four artificial and fourteen public benchmark data sets demonstrate that the LapLDM is superior to some well-known S3VM models.
Optimization of Fuzzy Logic Controller Used for a Differential Drive Wheeled Mobile Robot

The energy-efficient motion control of a mobile robot fueled by batteries is an especially important and difficult problem, which needs to be continually addressed in order to prolong the robot’s independent operation time. Thus, in this article, a full optimization process for a fuzzy logic controller (FLC) is proposed. The optimization process employs a genetic algorithm (GA) to minimize the energy consumption of a differential drive wheeled mobile robot (DDWMR) and still ensure its other performances of the motion control. The earlier approaches mainly focused on energy reduction by planning the shortest path whereas this approach aims to optimize the controller for minimizing acceleration of the robot during point-to-point movement and thus minimize the energy consumption. The proposed optimized controller is based on fuzzy logic systems. At first, an FLC has been designed based on the experiment and as well as an experience to navigate the DDWMR to a known destination by following the given path. Next, a full optimization process by using the GA is operated to automatically generate the best parameters of all membership functions for the FLC. To evaluate its effectiveness, a set of other well-known controllers have been implemented in Google Colab® and Jupyter platforms in Python language to compare them with each other. The simulation results have shown that about 110% reduction of the energy consumption was achieved using the proposed method compared to the best of six alternative controllers. Also, this simulation program has been published as an open-source code for all readers who want to continue in the research.
Vaccinium Species (Ericaceae): From Chemical Composition to Bio-Functional Activities

The genus Vaccinium L. (Ericaceae) includes more than 450 species, which mainly grow in cooler areas of the northern hemisphere. Vaccinium species have been used in traditional medicine of different cultures and the berries are widely consumed as food. Indeed, Vaccinium supplement-based herbal medicine and functional food, mainly from V. myrtillus and V. macrocarpon, are used in Europe and North America. Biological studies support traditional uses since, for many Vaccinium components, important biological functions have been described, including antioxidant, antitumor, anti-inflammatory, antidiabetic and endothelium protective activities. Vaccinium components, such as polyphenols, anthocyanins and flavonoids, are widely recognized as modulators of cellular pathways involved in pathological conditions, thus indicating that Vaccinium may be an important source of bioactive molecules. This review aims to better describe the bioactivity of Vaccinium species, focusing on anti-inflammatory and endothelial protective cellular pathways, modulated by their components, to better understand their importance for public health.
Pragmatic Analysis of Textbooks on the Basis of Speech Acts

This study investigatesfive speech acts of declaratives ,expressives, representatives, directives and commisives in three English textbooks at the level of III, IV and V published by Punjab Text Book Board Lahore in order to show whether theyareappropriate on pragmatic level for EFL learners or not. The results of the study reveal that thedistribution of all the speech acts is not equal both within each textbook andamong textbooks at all three levels. Among five speech acts, representative speech act occursthe most frequently in all textbooks while commissiveis the least used speech act. None of the books uses any speech act of declarative. This study implies that EFL teachers and materials designers shouldconsider pragmaticaspectsto improve the quality of both learning and instruction.
Complementary Metaresonator Sensor with Dual Notch Resonance for Evaluation of Vegetable Oils in C and X Bands

This paper investigates the effect of complementary metaresonator for evaluation of vegetable oils in C and X bands. Tremendously increasing technology demands the exploration of complementary metaresonators for high performance in the related bands. This research probes the complementary mirror-symmetric S resonator (CMSSR) that can operate in two bands with compact size and high sensitivity features. The prime motivation behind the proposed technique is to utilize the dual notch resonance to estimate the dielectric constant of the oil under test (OUT). The proposed sensor is designed on a compact 30×25 mm2 and 1.6 mm thick FR-4 substrate. A 50 Ω microstrip transmission line is printed on one side, while a unit cell of CMSSR is etched on the other side of the substrate to achieve dual notch resonance. A Teflon container is attached to CMSSR in the ground plane to act as a pool for the OUT. According to the simulated transmission spectrum, the proposed design manifested dual notch resonance precisely at 7.21 GHz (C band) and 8.97 GHz (X band). A prototype of complementary metaresonator sensor is fabricated and tested using CEYEAR AV3672D vector network analyzer. The comparison of measured and simulated data shows that the difference between the first resonance frequency is 0.01 GHz and the second is 0.04 GHz. Furthermore, a mathematical model is developed for the complementary metaresonator sensor to evaluate dielectric constant of the OUT in terms of the relevant, resonant frequency.
Intention to reuse M-Payment services: Lessons from the pandemic times

Mobile Payment (M-payment) is a relatively new type of service in developing nations, but it presents a vital role in the growth of economics in general. Therefore, evaluating the adoption level of mobile payment in the developing economy like Vietnam remains a meaningful topic. This study contributes a new explanation of the intention to reuse (INR) of individual consumers for M-payment services. Data has been analyzed using SmartPLS 3.3 that showed all seven hypotheses were to be supported. The finding of the study explains up to 56 percent INR of M-payment service. Moreover, the output contributes an outline strengthening of the reasonable combinations of Technology Readiness (TR), Customer Participation (CUP), Customer Empowerment (EMP), Customer Satisfaction (SAS), and Customer Trust (TRU) to Intention to Reuse (INR). Finally, the study proposes some crisis management insights and lessons for the banking sector during and after the COVID-19 pandemic.