Description Of Model Research Articles

Data-driven economic MPC with asymptotic stability and strong duality verification using Hankel matrix

We consider the problem of dynamic regulation with an economic cost function to control unknown linear systems, in which improving the economic performance and guaranteeing the stability of economical optimal equilibrium point are control objectives. A data-driven economic MPC scheme is presented using measured input-output trajectories without a prior system identification step. Our method uses Hankel matrices which include one input-output data trajectory for prediction in economic MPC, while persistently exciting of the input generating the data is needed. One of the novelties of the presented framework is directly verifying the strong duality property from input-output trajectory with the general cost function, considered as the supply rate. This is used to find a Lyapunov function for data-driven economic MPC. Under the strong duality assumption, asymptotic stability of the economical optimal equilibrium point for the closed-loop system with terminal equality constraint is guaranteed. The proposed data-driven economic MPC approach needs only persistently exciting data trajectory along with an upper bound on the system order and need no model description and no online parameter estimation. The proposed scheme applicability compared to the existing model-based economic MPC and data-driven MPC is illustrated for continuous stirred tank reactor (CSTR) and a numerical example and the robustness of the proposed scheme is evaluated in the case of measurement noise, as well as nonlinear model for CSTR system.

Earthquakes Three-Stage Early Warning and Short-Term Prediction

Among the anomalous geophysical phenomena observed preceding earthquakes, specific attention has been given to VLF/LF, ULF (very low frequency/low frequency, ultra-low frequency) electromagnetic (EM) emissions, recorded before earthquakes, because of an interesting correlation between them and seismic activity. Numerous scientific papers have been published on this topic, providing convincing evidence of these processes observed using ground-based and satellite ground-based observations during the preparation for the earthquake. These phenomena are detectable both at laboratory and geological scales. The authors of this paper have used an avalanche-like unstable geological model of fault formation and a model of the generation of electromagnetic emissions detected before the earthquakes to prove the prediction capabilities of VLF/LF EM emissions. The first gives a clear imagination of earthquake preparation in all stages in the focal area from the beginning of the micro-cracks appearing to the final formation of fault. Another one, based on electrodynamics, explains the EM emissions origination process and offers a formula that analytically connects the observed frequency of EM radiation with the linear size of the emitted body (fault). It is worth emphasizing the synthesis and rather harmonious relation of the mentioned models. Based on the above models conducted studies clearly show that the description of a qualitative avalanche-unstable geological model of fault formation using VLF/LF EM radiation data made it possible to quantitatively characterize the full cycle of preparation and occurrence of earthquake process. Namely, in the case of VLF/LF emissions monitoring, the beginning of the “avalanche process” of ruptures is considered the first stage of early warning of an incoming earthquake. The so-called EM emissions “silence” period is assessed as the second stage of early warning. The third early warning or an alarm about an incoming earthquake may be announced immediately at the moment of the first anomaly appearance subsequently the “silence” period. This article offers the method of earthquake three-step early warning and short-term (hourly) prediction.

Adaptive backstepping sliding mode subject-cooperative control for a pediatric lower-limb exoskeleton robot

The passive-assist rehabilitation mode with a fixed desired trajectory neglects the subject’s active involvement and degrades the therapeutic performance in case of partial muscle strength. Therefore, this study proposes a novel subject-cooperative control based on a variable admittance control scheme and a robust trajectory control scheme for a pediatric lower-limb exoskeleton robot. Initially, the system description and dynamic modeling are briefly explained. Thereafter, a neural-fuzzy–based variable admittance control ( nf VAC) is designed to incorporate a realistic subject-exoskeleton interaction and consider the subject’s active participation. Finally, a robust adaptive backstepping sliding mode control with rapid reaching law is used to handle parametric uncertainties and external disturbances. A stepwise selection of Lyapunov functions is utilized to address the stability of the trajectory control. The effectiveness of the proposed adaptive backstepping sliding mode–neural-fuzzy variable admittance control (ABSM- nf VAC) scheme is compared with two contrast control schemes, namely, adaptive backstepping-fixed admittance control (AB-FAC) and adaptive terminal sliding mode-fuzzy variable admittance control (ATSM- f VAC) for the active-assist mode with the effect of sudden reflex. Based on the numerical results, the suggested cooperative controller has demonstrated favorable tracking performance, compliant interaction, and safety aspects during gait training.

Intention to Use Mobile-Based Partograph and Its Predictors Among Obstetric Health Care Providers Working at Public Referral Hospitals in the Oromia Region of Ethiopia in 2022: Cross-Sectional Questionnaire Study.

A partograph is a pictorial representation of the relationship between cervical dilatation and the time used to diagnose prolonged and obstructed labor. However, the utilization of paper-based partograph is low and it is prone to documentation errors, which can be avoided with the use of electronic partographs. There is only limited information on the proportion of intention to use mobile-based partographs and its predictors. The objective of this study was to determine the proportion of obstetric health care providers at public referral hospitals in Oromia, Ethiopia, in 2022 who had the intention to use mobile-based partographs and to determine the predictors of their intention to use mobile-based partographs. We performed an institution-based cross-sectional study from June 1 to July 1, 2022. Census was conducted on 649 participants. A self-administered structured English questionnaire was used, and a 5% pretest was performed. Data were entered into EpiData version 4.6 and exported to SPSS version 25 for descriptive analysis and AMOS (analysis of moment structure; version 23) for structural and measurement model assessment. Descriptive and structural equation modeling analyses were performed. The hypotheses developed based on a modified Technology Acceptance Model were tested using path coefficients and P values <.05. About 65.7% (414/630; 95% CI 61.9%-69.4%) of the participants intended to use mobile-based electronic partographs, with a 97% (630/649) response rate. Perceived usefulness had a positive influence on intention to use (β=.184; P=.02) and attitude (β=.521; P=.002). Perceived ease of use had a positive influence on attitude (β=.382; P=.003), perceived usefulness (β=.503; P=.002), and intention to use (β=.369; P=.001). Job relevance had a positive influence on perceived usefulness (β=.408; P=.001) and intention to use (β=.185; P=.008). Attitude positively influenced intention to use (β=.309; P=.002). Subjective norms did not have a significant influence on perceived usefulness (β=.020; P=.61) and intention to use (β=-.066; P=.07). Two-thirds of the obstetric health care providers in our study intended to use mobile-based partographs. Perceived usefulness, perceived ease of use, job relevance, and attitude positively and significantly influenced their intention to use mobile-based electronic partographs. The development of a user-friendly mobile-based partograph that meets job and user expectations can enhance the intention to use.

EMOTIONAL INTELLIGENCE AND ITS ROLE IN PROMOTING ORGANIZATIONAL SUSTAINABILITY APPLIED STUDY-BABYLON ELECTRICITY DISTRIBUTION DIRECTORATE

The research aims to highlight the importance of emotional intelligence, which is one of the important topics that the majority of business institutions in general and educational institutions in particular may not focus on, perhaps due to the lack of awareness of its positive results affecting organizational sustainability. The research aims to address new elements different from what is familiar to know. The extent of its relationship and its impact on organizational sustainability, through a questionnaire designed for this purpose and distributed to a sample size of (56) employees in the Babylon Electricity Distribution Directorate. (50) samples were retrieved and the results were analyzed through descriptive statistical models and correlation. The research reached the following conclusions: There is a relationship between emotional intelligence and organizational sustainability.

Optical probing of ultrafast laser-induced solid-to-overdense-plasma transitions

Understanding the solid target dynamics resulting from the interaction with an ultrashort laser pulse is a challenging fundamental multi-physics problem involving atomic and solid-state physics, plasma physics, and laser physics. Knowledge of the initial interplay of the underlying processes is essential to many applications ranging from low-power laser regimes like laser-induced ablation to high-power laser regimes like laser-driven ion acceleration. Accessing the properties of the so-called pre-plasma formed as the laser pulse’s rising edge ionizes the target is complicated from the theoretical and experimental point of view, and many aspects of this laser-induced transition from solid to overdense plasma over picosecond timescales are still open questions. On the one hand, laser-driven ion acceleration requires precise control of the pre-plasma because the efficiency of the acceleration process crucially depends on the target properties at the arrival of the relativistic intensity peak of the pulse. On the other hand, efficient laser ablation requires, for example, preventing the so-called “plasma shielding”. By capturing the dynamics of the initial stage of the interaction, we report on a detailed visualization of the pre-plasma formation and evolution. Nanometer-thin diamond-like carbon foils are shown to transition from solid to plasma during the laser rising edge with intensities < 1016 W/cm². Single-shot near-infrared probe transmission measurements evidence sub-picosecond dynamics of an expanding plasma with densities above 1023 cm−3 (about 100 times the critical plasma density). The complementarity of a solid-state interaction model and kinetic plasma description provides deep insight into the interplay of initial ionization, collisions, and expansion.

Cooperative Adaptive Fuzzy Control for the Synchronization of Nonlinear Multi-Agent Systems under Input Saturation

This research explores the synchronization issue of leader–follower systems with multiple nonlinear agents, which operate under input saturation constraints. Each follower operates under a spectrum of unknown dynamic nonlinear systems with non-strict feedback. Additionally, due to the fact that the agents may be geographically dispersed or have different communication capabilities, only a subset of followers has direct communication with the leader. Compared to linear systems, nonlinear systems can provide a more detailed description of real-world physical models. However, input saturation is present in most real systems, due to various factors such as limited system energy and the physical constraints of the actuators. An auxiliary system of Nth order is introduced to counteract the impact of input saturation, which is then employed to create a collaborative controller. Due to the powerful capability of fuzzy logic systems in simulating complex nonlinear relationships, they are deployed to approximate the enigmatic nonlinear functions intrinsic to the systems. A distributed adaptive fuzzy state feedback controller is designed by approximating the derivative of the virtual controller by filters. The proposed controller ensures the synchronization of all follower outputs with the leader output in the communication graph. It is shown that all signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking errors converge to a small neighborhood around the origin. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.

Description of a Murine Model of Pneumocystis Pneumonia.

Pneumocystis pneumonia is a serious lung infection caused by an original ubiquitous fungus with opportunistic behavior, referred to as Pneumocystis jirovecii. P. jirovecii is the second most common fungal agent among invasive fungal infections after Candida spp. Unfortunately, there is still an inability to culture P. jirovecii in vitro, and so a great impairment to improve knowledge on the pathogenesis of Pneumocystis pneumonia. In this context, animal models have a high value to address complex interplay between Pneumocystis and the components of the host immune system. Here, we propose a protocol for a murine model of Pneumocystis pneumonia. Animals become susceptible to Pneumocystis by acquiring an immunocompromised status induced by iterative administration of steroids within drinking water. Thereafter, the experimental infection is completed by an intranasal challenge with homogenates of mouse lungs containing Pneumocystis murina. The onset of clinical signs occurs within 5weeks following the infectious challenge and immunosuppression can then be withdrawn. At termination, lungs and bronchoalveolar lavage (BAL) fluids from infected mice are analyzed for fungal load (qPCR) and immune response (flow cytometry and biochemical assays). The model is a useful tool in studies focusing on immune responses initiated after the establishment of Pneumocystis pneumonia.

Investigating different carbon-based target materials: Can we improve ionization in HiPIMS for the deposition of diamondlike carbon films?

Investigating different carbon-based target materials: Can we improve ionization in HiPIMS for the deposition of diamondlike carbon films?

Exploring the dynamics of physician-patient relationships: Factors affecting patient satisfaction and complaints.

This review identifes the factors influencing the relationship between physicians and patients that can lead to patients' dissatisfaction and medical complaints. Utilizing a systemic approach 92 studies were retrieved which included quantitative, qualitative, and mixed method studies. Through a thematic analysis of the literature, we identified three interrelated main themes that can influence the relationship between physicians and patients, patients' satisfaction, and the decision to file a medico-legal complaint. The main themes include patient and physician characteristics; the interpersonal relationship between physicians and patients; and the health care system and policies, with relevant subthemes. These themes are demonstrated in a descriptive model. The review suggests areas of focus for physicians who may wish to increase their awareness around the potential sources of relational problems with their patients. Identifying these issues may assist in improvements in the therapeutic relationship with patients, can reduce their medico-legal risk, and enhance the quality of their clinical practice. The findings can also be utilized to support andragogical principles for medical learners. The article can serve as a structured framework to identify potential problems and gaps to design and test effective interventions to mitigate these potential relational problems between physician-patient.

The neural oscillatory mechanism underlying human brain fingerprint recognition using a portable EEG acquisition device

In recent years, brainprint recognition has emerged as a novel method of personal identity verification. Although studies have demonstrated the feasibility of this technology, some limitations hinder its further development into the society, such as insufficient efficiency (extended wear time for multi-channel EEG cap), complex experimental paradigms (more time in learning and completing experiments), and unclear neurobiological characteristics (lack of intuitive biomarkers and an inability to eliminate the impact of noise on individual differences). Overall, these limitations are due to the incomplete understanding of the underlying neural mechanisms. Therefore, this study aims to investigate the neural mechanisms behind brainwave recognition and simplify the operation process. We recorded prefrontal resting-state EEG data from 40 participants, which is followed up over nine months using a single-channel portable brainwave device. We found that portable devices can effectively and stably capture the characteristics of different subjects in the alpha band (8-13Hz) over long periods, as well as capturing their individual differences (no alpha peak, 1 alpha peak, or 2 alpha peaks). Through correlation analysis, alpha-band activity can reveal the uniqueness of the subjects compared to others within one minute. We further used a descriptive model to dissect the oscillatory and non-oscillatory components in the alpha band, demonstrating the different contributions of fine oscillatory features to individual differences (especially amplitude and bandwidth). Our study validated the feasibility of portable brainwave devices in brainwave recognition and the underlying neural oscillation mechanisms. The fine characteristics of various alpha oscillations will contribute to the accuracy of brainwave recognition, providing new insights for the development of future brainwave recognition technology.

An instructional model text mapping with poetry text description

The Indonesian language learning method at Junior High School (SMP) Negeri Padangpanjang was generally boring and traditional. A solution is required to create products that are successful, efficient and enjoyable to use in classroom learning activities. A solution is required to make goods that are effective, efficient and entertaining to use in classroom learning activities. The product trial took place at SMP Negeri 3 Padangpanjang. The 4-D development phase was done in this study. During the conceptualization and development phases of this study, junior high school teachers and students were involved. In addition, experts participate in the process of evaluating products. A variety of methods are used including tests, questionnaires, observations and interviews. The main syntax of OMEMPAT is created by the descriptive text mapping learning model with the help of poetry text such as (1) orientation (2) reading and listening to poetry (3) mapping the contents of the descriptive text (4) presenting the results of the descriptive text mapping and (5) reflecting on the learning process. The three criteria of validity, practicability and efficacy were used to assess the quality of the learning model. The descriptive text mapping learning model which is supported by poetry texts needs to be put into practice. Teachers must create learning models that enable students to engage in educational activities while enjoying.

IMPACT OF CREDIT, INTEREST RATE AND INFLATION ON SMALL AND MEDIUM ENTERPRISES PRODUCTIVITY IN NIGERIA

This study sought to evaluate the impact of credit, interest rate and inflation on Small and Medium Enterprises Productivity in Nigeria, using annual time series data from 1986-2023. The data for the study was sourced from the World Development Indicator (WDI) and the Central Bank of Nigeria (CBN) statistical bulletin. The data collected were gross domestic product (GDP) which is the dependent variable while commercial bank total credit to private sector (CPS), small and medium enterprises contribution to GDP (SMEC), inflation rate (INFL) and interest rate (INT) are the independent variables. Descriptive, inferential statistics and Error Correction Model (ECM) were used to test the long run relationship of the variables. The results of the regression show that credit to private sector and small and medium enterprises contribution to gross domestic product is positive and significant to economic growth. The results further revealed that inflation rate and interest rate have a negative and insignificant effect on gross domestic product. The study recommends that government should put more efforts to curb inflation to give more confident to investors and should implement measures (low interest rates) that would broaden the borrowing base to improve financial capacity of SMEs, thus lead to an increase in the contribution of SMEs to nations GDP. KEYWORD: SME, Interest rate, Inflation, GDP.

Evolution of quadrupole-octupole collectivity in the even-even 54 ≤ Z ≤ 58 nuclei

Abstract We explore the quadrupole-octupole collectivity in the mass region of even-even 54 ≤ Z ≤ 58 (Xe, Ba and Ce) nuclei by analysing the fine structure of energy spectra. As a basic criterion for the presence of reflection-asymmetric degree of freedom we consider the formation of alternating-parity level-sequences. As a clearcut criterion for the emergence of pronounced octupole deformation we consider the reduction of the parity-shift at certain angular momentum and the formation of a single energy sequence which can be interpreted as an octupole band. Applying these criteria we select out alternating-parity bands (APBs) in the region of Xe, Ba and Ce isotopes for which a manifestation of pronounced octupole collectivity can be considered. Their fine structure is probed in a collective quadrupole-octupole rotation model (QORM) providing a detailed analysis in terms of odd-even staggering diagrams. The obtained model descriptions of the energy levels and staggering patterns reveal the most characteristic features of the quadrupole-octupole deformations in this mass region and outline a clearly determined area of manifestation of nuclear reflection-asymmetric shapes.&amp;#xD;

A damage constitutive model for consistent description of static and fatigue behaviors of ultra-high performance concrete containing coarse aggregate

A suitable constitutive model for describing the damage behavior of ultra-high performance concrete (UHPC) under various loading histories plays a vital role in analyzing its structural performance. In this work, a consistent elastoplastic damage model is developed for UHPC containing coarse aggregate (UHPC-CA) subjected to static and fatigue loads, in which the driving and alleviating effects induced by the inclusions of coarse aggregate and steel fiber are considered. For damage evolution, based on the acting mechanism of the non-uniformity of stress wave propagation determined by the loading rate on the mechanical responses of UHPC-CA, the loading rate is skillfully integrated into the damage evolution rule to achieve the consistent description of mechanical behaviors of UHPC-CA under static and fatigue loading conditions. Regarding plasticity growth, an empirical plastic deformation model is adopted to improve the computational efficiency of structural nonlinear analysis. To verify the applicability of the proposed model, a user-defined UMAT subroutine is further developed for the subsequent numerical implementation. The comprehensive comparisons between the numerical predictions and independent experimental results at both the material level and structural level solidly demonstrate the capacity of the consistent model to capture the main features concerning the mechanical performance of UHPC-CA subjected to different loading paths.

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

The design of a helicopter involves multiple disciplines and a large number of technical parameters with conflicting objectives, leading to the challenges of multidisciplinary coupling in design and optimization. In the context of the application of Model-Based Systems Engineering (MBSE) in complex product design, how to bridge the gap between MBSE and Multidisciplinary Design Analysis and Optimization (MDAO) to accelerate the early design process of helicopters remains an urgent problem to be addressed. The paper proposed an optimization framework that links MBSE and MDAO models for the design optimization problem of helicopters. On the MBSE side, the design optimization problem of helicopters was defined through the descriptive SysML model. On the MDAO side, the specific domain analysis model and optimization analysis workflow were established. The integration of design data was achieved through stereotype plugins and design components, bridging the gap between MBSE and MDAO, and providing accurate engineering data for system design verification. The paper provided an optimization case of a helicopter, with the optimal mission performance of the helicopter as the objective function. Through MDAO analysis, the design optimization of fuel consumption, take-off weight, and rotor dynamics parameters was completed, achieving an integrated process of system design and optimization.

Preoperative Risk Factors for 1-year Mortality in Patients Undergoing Fenestrated Endovascular Aortic Aneurysm Repair in the US-Aortic Research Consortium

BackgroundEarly survival (1-year) following elective repair of complex abdominal aortic aneurysms (AAA) or thoracoabdominal aortic aneurysms (TAAA) can be utilized as an indicator of successful repair and provides a reasonable countermeasure to the annual rupture risk based on diameter. We aimed to identify preoperative factors associated with 1-year mortality following F/BEVAR and develop a predictive model for 1-year mortality based on patient-specific risk-profiles. MethodsThe US-Aortic Research Consortium (US-ARC) database was queried for all patients undergoing elective F/BEVAR for complex AAA or TAAA from 2005-2022. The primary outcome was 1-year survival based on preoperative risk-profile. Multivariable Cox regression was used to determine preoperative variables associated with 1-year mortality overall and by extent of aortic pathology. Logistic regression was performed to build a predictive model for 1-year mortality based on number of risk factors present. ResultsA total of 2,099 patients met the inclusion criteria for this study (complex AAA: N=709, 34.3%; Type 1-3 TAAA: N=777, 37.6%; Type 4-5 TAAA: N=580, 28.1%). Multivariable Cox regression identified the following significant risk factors associated with 1-year mortality: current smoker, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), Aortic diameter>7cm, Age>75, Extent 1-3, creatinine>1.7mg/dL, and hematocrit<36%. When stratified by extent of aortic involvement, multivariable Cox regression revealed risk factors for 1-year mortality in complex AAA (CHF max aortic diameter>7cm, hematocrit<36mg/dL, and current smoking status), Type 1-3 TAAA (COPD, CHF, and Age>75) and Type 4-5 TAAA (age>75, creatinine>1.7mg/dL, and hematocrit<36mg/dL). Logistic regression was then utilized to develop a predictive model for 1-year mortality based on patient risk-profile. Appraisal of the model revealed an area under the curve of 0.64, p-value<0.001, and observed to expected ratio of 0.85. ConclusionsThis study describes multiple risk factors associated with an increase in 1-year mortality following F/BEVAR. Given that elective repair of complex AAA or TAAA is offered to some patients in whom future rupture risk outweighs operative risk, these findings suggest that highly comorbid patients with smaller aneurysms may not benefit from repair. Descriptive and predictive models for 1-year mortality based on patient risk-profiles can serve as an adjunct in clinical decision-making when considering elective F/BEVAR.

A Popular Topic Detection Method based on Microblog Images and Short Text Information

Popular topic detection is a topic identification by the information of documents posted by users in social networking platforms. In a large body of research literature, most popular topic detection methods identify the distribution of unknown topics by integrating information from documents based on social networking platforms. However, among these popular topic detection methods, most of them have a low accuracy in topic detection due to the short text content and the abundance of useless punctuation marks and emoticons. Image information in short texts has also been overlooked, while this information may contain the real topic matter of the user's posted content. In order to solve the above problems and improve the quality of topic detection, this paper proposes a popular topic detection method based on microblog images and short text information. The method uses an image description model to obtain more information about short texts, identifies hot words by a new word discovery algorithm in the preprocessing stage, and uses a PTM model to improve the quality and effectiveness of topic detection during topic detection and aggregation. The experimental results show that the topic detection method in this paper improves the values of evaluation indicators compared with the other three topic detection methods. In conclusion, the popular topic detection method proposed in this paper can improve the performance of topic detection by integrating microblog images and short text information, and outperforms other topic detection methods selected in this paper.

The Land Component LM4.1 of the GFDL Earth System Model ESM4.1: Model Description and Characteristics of Land Surface Climate and Carbon Cycling in the Historical Simulation

AbstractWe describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Land Model version 4.1 (LM4.1), which builds on component and coupled model developments over 2013–2019 for the coupled carbon‐chemistry‐climate Earth System Model Version 4.1 (ESM4.1) simulation as part of the sixth phase of the Coupled Model Intercomparison Project. Analysis of ESM4.1/LM4.1 is focused on biophysical and biogeochemical processes and interactions with climate. Key features include advanced vegetation dynamics and multi‐layer canopy energy and moisture exchanges, daily fire, land use representation, and dynamic atmospheric dust coupling. We compare LM4.1 performance in the GFDL Earth System Model (ESM) configuration ESM4.1 to the previous generation component LM3.0 in the ESM2G configuration. ESM4.1/LM4.1 provides significant improvement in the treatment of ecological processes from GFDL's previous generation models. However, ESM4.1/LM4.1 likely overestimates the influence of land use and land cover change on vegetation characteristics, particularly on pasturelands, as it overestimates the competitiveness of grasses versus trees in the tropics, and as a result, underestimates present‐day biomass and carbon uptake in comparison to observations.

Teachers' Opinions on Second Grade Language Skills of Students Who Learned Initial Literacy Through Distance Education

This study examines teachers' opinions on how the language skills in the second grade (listening, speaking, reading, writing) of students who learned initial literacy in the first grade of elementary school (2020-2021) through distance education due to the pandemic were affected. This study was conducted using a descriptive qualitative research model. The study group comprised 18 teachers who conducted first-grade initial literacy teaching via distance education in 2020-2021 academic year and worked in the second grade during 2021-2022 academic year. Each teacher had instructed first grade at least three times in their career. A semi-structured interview form served as the data collection tool, and thematic analysis was employed for data analysis. The data yielded four themes: listening skills, speaking skills, reading skills, and writing skills, with corresponding sub-themes identified and interpreted. Participants reported that the pandemic led to temporary school closures and a shift from face-to-face to distance learning for first-grade literacy. Consequently, students missed the opportunity to develop listening, speaking, reading, and writing skills through direct interaction in the classroom. They stated the limitations and conditions of distance education were cited as reasons for this shortfall. As a result, they stated that there are inadequacies in students' listening, speaking, reading and writing skills, and that these inadequacies have a negative impact on their listening skills in the second grade. This resulted in inadequacies in students' listening, speaking, reading, and writing skills, negatively impacting their second-grade. It was reported that there were lack of gains in the achievements of this group compared to the students of previous years, and that these were due to the fact that the initial literacy teaching was carried out through distance education.