Extensive Instruction Research Articles

Level of Implementation by Rural Women in Bashiqa District of Extension Instructions Related to Rationalization of Water Consumption

This study aimed to determine the level of implementation of rural women in Bashiqa area of the extension instructions related to rationalising water consumption in Bashiqa area / Nineveh Governorate / Iraq, in addition to determining the correlation between the level of implementation of this activity with a number of independent variables. The study also aimed to determine the level of obstacles facing women's implementation of the extension instructions, the research tool consisted of three parts, where the first part included a number of personal factors, while the second part consisted of 20 paragraphs related to rationalising water use and the third part related to obstacles, which numbered 8 paragraphs, and The stability coefficient of the questionnaire extracted by the Cronbach's alpha method was 0. The research sample consisted of 140 randomly selected female respondents from 24 villages of Bashiqa district. spss and excel software were used to tabulate, classify and analyse the data, and the results showed that 77% of the respondents' application of the extension instructions is moderate and tends to decrease, and there was a significant positive correlation between the dependent factor and two variables (number of children in the family, family ownership of an alarm device It was also found that there is a significant negative correlation between the dependent factor and the two variables (age, the family owns a water well in the garden of the house), and the results indicated that there are moderate and tend to be significant obstacles that hinder the implementation of the extension instructions to reduce water consumption by the female community, and the study finally provided a number of conclusions and recommendations.

Assessing the prevalence of unused medicines at home and associated factors: a community-based cross-sectional study

BackgroundPrescriptions come with extensive instructions on taking medicines but provide little information about the burden of unused medicines. This issue centers around the vast quantities of unused medications accumulated in households. The study aimed to assess the prevalence of unused medicines and associated factors in Gondar City.MethodThe study was conducted through a community-based cross-sectional survey in Gondar City from July 30 to August 30, 2023. The data was collected using the Kobo toolbox, exported into an Excel sheet, and then analyzed using SPSS version 27 software. Both multivariate and bivariate binary logistic regressions were performed in the data analysis. A p-value of 0.05 with a 95% confidence interval was used to determine statistical significance.ResultThe study interviewed 786 participants, with a 92.8% response rate. 55% of the 786 households surveyed kept unused medications at home, most commonly antibiotics (37%), antipyretics (17.6%), and analgesics (15%). Factors associated with having unused medicines at home included not receiving medication information (AOR = 2.327, 95% CI: 1.535, 3.527), having a chronic disease (AOR = 5.897, 95% CI: 3.667, 9.484), having health insurance coverage (AOR = 1.456, 95% CI: 1.036, 2.047), self-medicating with NSAIDs (AOR = 2.018, 95% CI: 1.396, 2.919), and poor disposal practices (AOR = 3.613, 95% CI: 2.546, 5.127).ConclusionThe study found a considerable high prevalence of unused medications in Gondar City due to factors like lack of medication education, chronic conditions, insurance coverage, self-medication, and poor disposal practices. To address this, public education programs and safe disposal guidelines should be implemented to promote safer practices.

Comparison of the oral health status of nursing home residents using the current and the newly developed interRAI oral health section (OHS-interRAI): a cross-sectional study

BackgroundRegular dental l check-ups and good oral hygiene are challenging for nursing home residents, resulting in poor oral health. The interRAI instrument for Long-Term Care Facilities (LTCF) enables caregivers to evaluate residents’ health, including oral health, and to integrate oral care into general care planning. Because the current oral heal1th section in the interRAI instruments does not accurately identify residents who need help with daily oral care or dental referral, the interRAI Oral Health Section (OHS-interRAI) was developed. The OHS-interRAI differs from the current section by including more items, response options and guidelines, photographs, instruction videos, and Collaborative Action Points to alert caregivers when oral care is needed.This study describes and compares residents’ oral health status assessed by caregivers using the current section and the OHS-interRAI.MethodsThis cross-sectional study includes baseline data of adults aged 65 years or older in Flemish and Dutch nursing homes, collected by professional caregivers (e.g., nurses, nurse aids, therapists). Assessments with the current section dated from October 2016 to January 2023, and with the OHS-interRAI from October 2020 to January 2023.ResultsInterRAI assessments of 12,476 residents from 158 nursing homes with the current section were compared with those of 1212 residents from 37 nursing homes with the OHS-interRAI.The OHS-interRAI assessments showed more missing data. A higher proportion of oral health problems was detected with the OHS-interRAI compared to the current section for chewing function (13.7% vs. 6.8%), dry mouth (9.8% vs. 7.6%), teeth (22.1% vs. 16.6% ),and gums (7.8% vs. 3.1%). There was no significant difference in the proportion of residents with discomfort or pain in the mouth.ConclusionsMore missing OHS-interRAI data may be attributed to regulatory decisions on using the interRAI LTCF instrument. Caregivers identified more oral health problems with the OHS-interRAI, which may be due to its additional features, such as photographs and extensive instructions. The Collaborative Action Points included in the OHS-interRAI support continuity of care and enable integration of oral care into general care. Further research is needed to evaluate whether the OHS-interRAI accurately identifies residents who need help with daily oral hygiene or dental referral.

Seesaw: A 4096-bit vector processor for accelerating Kyber based on RISC-V ISA extensions

The ML-KEM standard based on Kyber algorithm is one of the post-quantum cryptography (PQC) standards released by the National Institute of Standards and Technology (NIST) to withstand quantum attacks. To increase throughput and reduce the execution time that is limited by the high computational complexity of the Kyber algorithm, an RISC-V-based processor Seesaw is designed to accelerate the Kyber algorithm. The 32 specialized extension instructions are mainly designed to enhance the parallel computing ability of the processor and accelerate all the processes of the Kyber algorithm by thoroughly analyzing its characteristics. Subsequently, by carefully designing hardware such as poly vector registers and algorithm execution units on the RISC-V processor, the support of microarchitecture for extension instructions was achieved. Seesaw supports 4096-bit vector calculations through its poly vector registers and execution unit to meet high-throughput requirements and is implemented on the field-programmable gate array (FPGA). In addition, we modify the compiler simultaneously to adapt to the instruction extension and execution of Seesaw. Experimental results indicate that the processor achieves a speed-up of 432× and 18864× for hash and NTT, respectively, compared with that without extension instructions and a speed-up of 5.6× for the execution of the Kyber algorithm compared with the advanced hardware design.

Wireless vision-based digital media fixed-point DSP processor depending robots for natural calamities

AbstractNatural calamities are affecting many parts of the world. Natural disasters, terrorist attacks, earthquakes, wildfires, floods and all unpredicted phenomena. Disasters cause emergency conditions, so imperative to coordinate the prompt delivery of essential services to the sufferers. Often, disasters lead many people to perish by becoming trapped inside, but many more also perish as a result of individuals receiving rescue either too late or not at all. The implementation and design of a Receiver module utilizing Davinci code processor DVM6437, Wireless camera receiver, Zigbee Transceiver and Global Positioning System (GPS) is proposed in this manuscript for Wireless Vision-based Semi-Autonomous rescue robots that are employed in rough terrain. The receiver side’s Zigbee transceiver module eliminates the limitations of tele-operating rescue robots by enabling the control station to receive GPS data signals and aids in robot management by sending control signals wirelessly. Half and full-duplex communication are supported by the Davinci processor DVM6437, a digital media fixed-point DSP processor that relies on Very Long Instruction Words. It includes an extensive instruction set that is ideal for real-time salvage operations. DVM processor is coded utilizing MATLAB Simulink. MATLAB codes and Simulink blocks are employed under Embedded IDE link.

First Steps towards Efficient Genome Assembly on ARM-Based HPC

Exponential advances in computational power have fueled advances in many disciplines, and biology is no exception. High-Performance Computing (HPC) is gaining traction as one of the essential tools in scientific research. Further advances to exascale capabilities will necessitate more energy-efficient hardware. In this article, we present our efforts to improve the efficiency of genome assembly on ARM-based HPC systems. We use vectorization to optimize the popular genome assembly pipeline of minimap2, miniasm, and Racon. We compare different implementations using the Scalable Vector Extension (SVE) instruction set architecture and evaluate their performance in different aspects. Additionally, we compare the performance of autovectorization to hand-tuned code with intrinsics. Lastly, we present the design of a CPU dispatcher included in the Racon consensus module that enables the automatic selection of the fastest instruction set supported by the utilized CPU. Our findings provide a promising direction for further optimization of genome assembly on ARM-based HPC systems.

Vectorization Programming Based on HR DSP Using SIMD

Single instruction multiple data (SIMD) vector extension has become an essential feature of high-performance processors. Architectures such as x86, ARM, MIPS, and PowerPC have specific vector extension instruction sets and SIMD micro-architectures. Using SIMD vectorization programming can significantly improve the performance of application algorithms while keeping the hardware overhead low. In addition, other methods can enhance algorithm performance, such as selecting the best SIMD vectorization model for algorithms, ensuring sufficient instruction streams, implementing reasonable and effective cache data prefetching, and aligning data access and storage addresses according to instruction characteristics. The goal of this paper is three-fold. First, we introduce the basic structural characteristics of a general RISC processor, Hua Rui (HR) DSP, with a custom vector instruction set based on compatibility with an MIPS64 fixed-point and floating-point instruction set, as well as a Fei Teng (FT) processor compatible with an ARMv8 instruction set. Second, we summarize the fundamental principles of SIMD vectorization programming design for the HR DSP, which provides ideas for other scholars or engineering and technical personnel to study the algorithm performance using SIMD vectorization optimization. Third, we implement representative typical algorithms based on the HR and FT platforms and obtain experimental results that show improvement in algorithm SIMD vectorization optimization according to the vector programming design principles summarized in this article can improve the single-core performance of scalar implementation without vectorization, instruction streams, and cache data prefetching by 4–22 times for mean filter, accumulation, and matrix–matrix multiplication, which is significantly better than the performance improvement of 3–13 times for the FT platform. Moreover, the performance of matrix–matrix multiplication using the best vectorization model on the HR platform is about 84% higher than that of the common SIMD vectorization model.

Algorithms for Improving the Automatically Synthesized Instruction Set of an Extensible Processor

Processors with extensible instruction sets are often used today as programmable hardware accelerators for various domains. When extending RISC-V and other similar extensible processor architectures, the task of designing specialized instructions arises. This task can be solved automatically by using instruction synthesis algorithms. In this paper, we consider algorithms that can be used in addition to the known approaches and improve the synthesized instruction sets by recomputing common operations (the result of which is consumed by multiple operations) of a program inside clustered synthesized instructions (common operations clustering algorithm), and by identifying redundant (which have equivalents among the other instructions) synthesized instructions (subsuming functions algorithm). Experimental evaluations of the developed algorithms are presented for the tests from the domains of cryptography and three-dimensional graphics. For Magma cipher test, the common operations clustering algorithm allows reducing the size of the compiled code by 9 %, and the subsuming functions algorithm allows reducing the synthesized instruction set extension size by 2 times. For AES cipher test, the common operations clustering algorithm allows reducing the size of the compiled code by 10 %, and the subsuming functions algorithm allows reducing the synthesized instruction set extension size by 2.5 times. Finally, for the instruction set extension from Volume Ray-Casting test, the additional use of subsuming functions algorithm allows reducing problem-specific instruction extension set size from 5 to only 2 instructions without losing its functionality.

Developing a Theory-Based Summative Testing Approach to Evaluate a Mobile Health App for Older Adults

We describe a method of selecting and organizing tasks for summative testing of a new mobile health (mHealth) app by older adults. Summative evaluations of mobile health apps often focus on “ease of use” assessed by time to complete tasks and the number of use errors. This is not an optimal approach for older users who are more likely to have slower response times and be less experienced with these technologies. In testing with older users, it is important to incorporate the expected process of learning a new app without the use of training or extensive instructions. We drew on the theories of Mastery Learning, Cognitive Load, and Teach to Goal to inform our selection of tasks and the organization of task scenarios to better simulate the users’ patterns of exploration, learning, and initial use of a mobile app. This research has general relevance for human factors professionals involved in planning, conducting, and reporting the findings from summative evaluations for a broad range of mHealth apps and user groups.

The role of language aptitude probed within extensive instruction experience: morphosyntactic knowledge of advanced users of L2 English

Abstract This study investigated the role of language aptitude for participants with extensive instructed L2 English learning experience in judging the grammaticality of sentences in auditory and written modalities. Partially replicating a naturalistic L2 learning study, we administered written and auditory grammaticality judgement tests in L2 English and the LLAMA aptitude tests to 37 students at an English-medium state university in Turkey. The participants were divided into higher and lower aptitude groups based on LLAMA scores, and their accuracy/response time scores in early/intermediate/late-acquired structures were examined. The results showed that aptitude was significantly associated with performance only in late-acquired structures in the written modality. Additionally, aptitude distinguished response time rather than accuracy scores, suggesting a qualitative processing difference. The explicit and analytic nature of language aptitude was discussed for adult learners, which is more relevant for the Turkish context where English is taught as a foreign language in academic settings.

Juvenile Justice and Women's Clubs: Ogden as a Case Study

Juvenile Justice and Women's Clubs: Ogden as a Case Study

Surfaltr: An R/Bioconductor package to benchmark surface protein isoforms by rapid prediction and visualization of transmembrane topologies.

Cell surface proteins form a major fraction of the druggable proteome and can be used for tissue-specific delivery of oligonucleotide/cell-based therapeutics. Surface protein isoforms are regulated by alternative splicing, which drives subcellular localization and transmembrane (TM) topology thereby shaping cell type specific signatures. Current advances in multiomic approaches have developed interest in discovery of tissue-specific alternatively spliced or novel surface protein isoforms. However, there exists a need for bioinformatic approaches for rapidly benchmarking the large number of isoforms identified by these approaches. To address this gap, we have developed, surfaltr, an R package which takes user input isoforms, pairs them with the known principal isoform of the gene, predicts TM topologies, and generates a customizable graphical output. Further, surfaltr facilitates prioritization of topologically diverse isoform pairs through incorporation of three different ranking metrics and through protein alignment functions. Here, we demonstrate the utility of our R package by evaluating the mouse retina-specific novel surface protein isoforms identified in Ray etal. 2020. surfaltr is freely available through Bioconductor (https://bioconductor.org/packages/surfaltr) and the vignette provides extensive instructions for implementation.

The Peti and the Power of Speech in Proverbs 1-9

Speech is a prominent theme throughout ancient Near Eastern wisdom literature. Accordingly, the proverbs in Proverbs 10-29 offer extensive instruction about the nature and power of speech. Speech also pervades Proverbs 1-9, a series of instructive lectures and interludes. However, speech is not primarily a topic of instruction; rather, it is a vehicle for instruction. Proverbs 1-9 puts speech on the lips of competing voices-the father, the gang, the seductress, Lady Wisdom, and Lady Folly-and admonishes, seduces, and encourages the son (the peti), who is presented with a choice: To whom will he listen? These chapters draw attention to what might be considered the most important trait of the peti: being a discerning listener. This article argues that, by prefacing the instruction of chapters 10-29 with chapters 1-9, the compiler of Proverbs sets discernment as the fundamental requirement for the instruction that follows. It surveys the topic of "speech" in ancient Egyptian wisdom literature; examines "speech" proverbs in Proverbs 10-29; and evaluates how "speech " in Proverbs 1-9 contributes to the portrayal of a teachable peti and one's approach to the rest of the book.

Adolescents' expectancy-value profiles in school context: The impact of self-directed learning intervals.

Using the situated expectancy-value theory, it becomes possible to explain motivational functioning across alternating learning conditions not only at a particular moment but also over time. The situated expectancy-value theory provides evidence for the critical role of context. The present research examines how adolescents' success expectancies, task values, and effort develop when the conditions of the academic environment change. It also evaluates whether adolescents adopt more adaptive expectancy-value profiles in response to the need-based nature of self-directed learning as an extension of regular instruction. Within the self-directed learning approach under investigation, adolescents take responsibility for their own learning processes. The present research offers insights into the expectancy-value profiles of 754 German adolescents (Mage = 13.56; SD = 1.2; 49.4% female). A four-wave study was used to examine perceptions of self-efficacy, intrinsic value, utility value, and effort. Latent profile analyses and latent transition analyses were employed. Notably, the results provide evidence that expanding instruction via self-directed learning intervals that occur for 1 week per semester contributes to more favorable expectancy-value profiles within a student's favorite subject. A mixed profile (highly confident, hardly interested) disappeared. Instead, success expectations aligned more closely with adolescents' task values and effort. All profiles settled at a higher level. The findings indicate that instruction that is expanded via self-directed learning intervals has positive consequences for motivational profiles over time. An initial self-directed learning episode led to a shift to more interested profile groups. The continuation of a positive trend even after a self-directed learning interval indicates that adolescents are able to continually adapt their learning to their needs during teacher-directed instruction. This study provides clues about how to design curricula in a way that counteracts the downward trend in students' motivation to learn.

Social Media Platforms as Pedagogical Tools in Language Acquisition

Social media has livened the digital world with its numerous modern features in communication, media sharing, and entertainment elements. As a part of the continuous search for effective and efficient ways of instruction, this review aimed to describe social media as a pedagogical tool in language acquisition. The methodology used was patterned to Arksey and O'Malley's (2005) approach to reviewing the literature. Fifteen (15) research articles published in online journals were reviewed to describe the effectiveness of social media when utilized as a pedagogical tool in language acquisition. Results of the review showed that social media is primarily used for communication, collaborative learning, and extension of learning practice. Writing skills and vocabulary are the primary skills developed in using social media platforms such as Facebook which is the most frequently used app for language learning. Participants of the studies show a positive attitude toward the integration of social media into language acquisition. In a conclusion, various social media apps and sites exhibit promising influence on language learning not only in formal education but as well as the extension of instruction outside schools.

Embedded Microprocessor Extension Design and Optimization for Real-Time Edge Computing

With the development of 5G communication technology, more and more applications could be integrated into one system. Edge computing system and mixed-criticality system may integrate tasks of different criticality levels, which brings better balance in isolation and performance. Such advantages make it gradually become a research hotspot in edge computing and real-time systems with 5G. The important content of designing a mixed-criticality system is how to reduce interference between tasks and how to schedule tasks efficiently to ensure that tasks of different criticality levels can meet time constraints. Instruction extension and hardware software cooperative support may be an effective solution. Based on a fine-grained multithreaded RISC-V processor, this article gives some extensions for real-time operations and proposes a hardware software cooperative real-time scheduling mechanism. Experimental results show that, compared with FlexPRET hardware, the performance of thread scheduling is improved by 22.94% on average. Compared with software scheduling, the performance of scheduling same programs and multiple programs are improved by 15.46% and 26.00%, respectively.

Cross-Modal Dynamic Networks for Video Moment Retrieval With Text Query

Video moment retrieval with text query aims to retrieve the most relevant segment from the whole video based on the given text query. It is a challenging cross-modal alignment task due to the huge gap between visual and linguistic modalities and the noise generated by manual labeling of time segments. Most of the existing works only use language information in the cross-modal fusion stage, neglecting that language information plays an important role in the retrieval stage. Besides, these works roughly compress the visual information in the video clips to reduce the computation cost which loses subtle video information in the long video. In this paper, we propose a novel model termed Cross-modal Dynamic Networks (CDN) which dynamically generates convolution kernel by visual and language features. In the feature extraction stage, we also propose a frame selection module to capture the subtle video information in the video segment. By this approach, the CDN can reduce the impact of the visual noise without significantly increasing the computation cost and leads to a better video moment retrieval result. The experiments on two challenge datasets, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , Charades-STA and TACoS, show that our proposed CDN method outperforms a bundle of state-of-the-art methods with more accurately retrieved moment video clips. The implementation code and extensive instruction of our proposed CDN method are provided at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/CFM-MSG/Code_CDN</uri> .

Analysis of an Application Specific Instruction-set Processor's expansion potential, considering performance and implementation effort

Modern embedded systems need to provide high compute power while being energy efficient. This can be achieved by domain specific processing cores and accelerators that have been optimized for a specific class of applications. The optimizations can be introduced in the structure of the memory system, the instruction set architecture, special instructions that are provided and in the interfaces that allow the coupling of external accelerators. In this work we investigated the opportunities to adopt a processor by introducing different instruction set extensions, the creation of manually designed instruction extensions for special applications and the extension of the core by a Very Large Instruction Word (VLIW) extension. All modifications have been analyzed using a benchmark suite with applications from different domains. In addition to performance measurements, we rated the effort, that specific extensions introduce to the hard- and the software-designer. All experiments have been done using the Cadence Tensilica Xtensa LX Application Specific Instruction-set Processor (ASIP) in the cycle-accurate simulation mode. Or work shows, that speedups of 4x can be reached by just adding around 10% of gates to the processor. For this kind of analysis, we show an evaluation methodology and introduce a metric.

Government and University Partner for Virtual Service-Learning to Support Intergenerational Social Interaction

Pre-pandemic, evidence existed that intergenerational service-learning programs support knowledge of aging and positive attitudes and perceptions (Monahan et al., 2020). As spring 2020 COVID-19 lock downs and public health warnings urged physical distancing of community dwelling older adults, growing concern about the unintended consequences of increased social isolation on mental and physical health prompted the Secretary’s Office of Pennsylvania Department of Aging to design a pilot project with university faculty for virtual intergenerational social interaction. The Department identified older adults at the highest risk for social isolation (live alone, in poverty, with a disability). The resulting pilot project is fully integrated as a high impact practice into eight sections of recreational therapy and gerontology courses with participation by 210 undergraduate students and 210 older adults for 9 weeks of both the fall and spring semesters. Students, who received extensive classroom instruction aimed at avoiding negative stereotypes of older adults as helpless and dependent, called their assigned partner several times a week for at least an hour of communication. Using the UCLA loneliness scale, community-dwelling older adults reported frustration with isolation due to the pandemic. Those with low and moderate loneliness reported positive feelings about program and looking forward to interactions with students. Students gained virtual communication skills that may contribute to telehealth competencies, intervention skills such as assessment, life review/reminiscence, mindfulness techniques, and leisure education. Moreover, an analysis of student reflections revealed positive changes in attitudes toward older adults and the ability to enjoy common interests despite age differences.

The forms, functions, and uses of praise in self-contained classrooms: a qualitative examination

Special education teachers are often encouraged to use praise in their instructional interactions with their students with significant support needs (SSN). It is assumed that reinforcing behavior facilitates learning and academic achievement for these students. Despite a myriad of interventions aimed at increasing special education teachers’ use of praise, little is known about how praise functions in this context. This is concerning, given the growing body of literature suggesting that praise negatively impacts academic achievement for students without SSN. This study uses constant comparative methods to examine the form, function, and use of praise in supporting learning and instruction in two special educations classrooms that exclusively serve students with SSN. Findings indicate that praise, as an extension of instruction that prioritizes compliance over learning, did little to engage students in thinking or learning. The results hold implications for the instructional approaches teachers use with their students with SSN.