Terms Of Recognition Research Articles

Intelligent mining of safety hazard information from construction documents using semantic similarity and information entropy

Project construction on-site is known to be very dangerous workplace environments due to large numbers of safety hazards. Analysis of construction safety hazards is essential to formulate rational safety management plans and prevent accidents. Construction documents contain large volumes of safety hazard information available for analysis. However, such analyses are challenging because the safety hazard information in the construction documents is presented in an unstructured or semi-structured format. This study proposes a method for intelligent mining of safety hazard information, which comprises safety hazard technical term recognition and safety hazard information analysis. The safety hazard technical term recognition model is developed based on semantic similarity and information correlation to build a safety hazard technical term library. The safety hazard information based on the technical term library is mined and analyzed using the term frequency-inverse document frequency method (TF-IDF). Finally, the proposed method is applied to build the safety hazard technical term library, which contains 2697 technical terms, and develop a hydraulic project construction safety hazard analysis system, which can realize the intelligent recognition and application of technical terms. Meanwhile, this system can automatically extract safety hazard information and provide a visualization interface to intuitively show the safety hazard analysis results, which improves the extraction efficiency of safety hazard information. The study provides a new approach for recognizing technical terms and mining safety hazard information, which can lead to enhancing management efficiency and practical knowledge discovery for safety management.

Edible Coatings Based on a Furcellaran and Gelatin Extract with Herb Addition as an Active Packaging for Carp Fillets

This is the first such study in which a gelatin extract obtained from carp skins enriched with dry herbs (thyme or rosemary) has been prepared. Extracts prepared in such a manner were added to furcellaran coatings. Coatings were tested for their mechanical properties and the obtained results showed that the control coatings, and those with the addition of rosemary, had the best strength-related parameters. A new ready-to-cook product was evaluated with regard to the preservative effects of carp skin gelatin coatings containing rosemary and thyme extracts in terms of pH, biogenic amine formulation, microbial changes and sensorial characteristics. The coatings with added rosemary proved effective in inhibiting the formation of biogenic amines, and slowing down the microbial deterioration of carp fillets (reduction by 0.53 and 0.29 log cfu/g). The evaluated herb coatings changed the characteristic taste of fish. Interestingly, the coatings emphasized the natural saltiness of fish meat.

In Vitro Antioxidant Activities of Plant Polyphenol Extracts and Their Combined Effect with Flaxseed on Raw and Cooked Breast Muscle Fatty Acid Content, Lipid Health Indices and Oxidative Stability in Slow-Growing Sasso Chickens.

Adding flaxseed was found to decrease oxidative stability in feed and increase the antioxidant needs of chicken. This has also been associated with a decrease in the nutritional value and oxidative stability of meat if sufficient dietary antioxidants are not included. Furthermore, dietary flaxseed has been explored in fast-growing chickens as such studies are limited with slow-growing chickens. Thus, this study aimed to evaluate the effects of feeding plant polyphenol extracts as an antioxidant alongside flaxseed on fatty acid content, oxidative stability, and lipid health indices in breast muscle of slow-growing Sasso T451A dual-purpose chicken. A total of 126 chickens assigned to six groups (seven replicates of three) were fed on NC (control and no antioxidants), FS (75 g flaxseed and no antioxidants), VE8 (75 g flaxseed and 800 mg vitamin E), TS8 (75 g flaxseed and 800 mg Thymus schimperi), DA8 (75 g flaxseed and 800 mg Dodonaea angustifolia) and CD8 (75 g flaxseed and 800 mg Curcuma domestica) extract per kg diet. Feeding on CD8 and VE8 in raw and TS8, CD8 and VE8 diets in cooked breast muscle increased (p < 0.05) the C22:6n − 3 (DHA) and C20:5n − 3 (EPA) contents compared to the FS diet. Feeding FS increased (p < 0.05) the malondialdehyde (MDA) content in breast muscle, whereas TS8 in cooked and raw and CD8 and DA8 diets in raw breast muscle decreased it (p < 0.05). No added benefit was observed in feeding VE8 over plant extracts in terms of improving fatty acid composition and lipid health indices and reducing lipid oxidation in breast meat.

Antibacterial, antioxidant, and phytochemical analysis of Piper longum fruit extracts against multi-drug resistant non-typhoidal Salmonella strains in vitro

Most bacteria are becoming resistant to almost all of the currently recommended drugs, leading to difficulty in their treatment. The present study focused on evaluating the therapeutic potential of Piper longum fruit extracts in terms of bactericidal, antioxidant and phytochemical evaluation by conducting antibacterial sensitivity tests against four multidrug-resistant Salmonella strains (Salmonella enterica subsp. arizonae, Salmonella Newport, Salmonella enterica ser. Typhi, and Salmonella enterica ser. Paratyphi) obtained from the Institute of Microbial Technology (IMTECH), Chandigarh. The Agar Well Diffusion method and the Minimum Inhibitory concentration (MIC) methods were performed to implement the anti-sensitivity test of crude extracts of the plant. The present study showed that the MIC of the P. longum was between 0.25-0.0625mg/ml, which was lowest in the aqueous extract at 0.5mg/100µl, and the highest in the methanol extract (1mg/100µl). The Minimum Bactericidal Concentration (MBC) was lowest in aqueous (0.5mg/100µl) and highest in methanol plant extract (1mg/100µl). The methanol extract had the maximum antibacterial potency, whereas the aqueous extract had the lowest. The antioxidant capacity of the plant extracts was determined using a DPPH assay. Methanol plant extract revealed the highest antioxidant power (81.92%) and the lowest was found in the aqueous extract (62.84%). The GC-MS approach identified active bioingredients, important botanicals including caryophyllene, eicosane, and piperazine (potent antibacterial agent) as naphthyridine (having antimicrobial, anticancer, and anti-inflammatory activities), among others. The unique aspect of the study was the effectiveness of P. longum against Salmonella strains that are resistant to multiple antibiotics. This suggests that P. longum can be a great source of novel antibacterial compound for the development of herbal formulations.

Farang (Psidium guajava L.) Dried Leaf Extracts: Phytochemical Profiles, Antioxidant, Anti-Diabetic, and Anti-Hemolytic Properties for Ruminant Health and Production.

Due to its advantageous antioxidant phytochemical components, Psidium guajava L. has become an indispensable plant in pharmaceutical formulations, playing a crucial role in safeguarding human health. On ruminant animals, however, there has been limited investigation. The purpose of this investigation was to assess the phytochemical profiles and biological potential of Farang (P. guajava L.) leaf extracts for ruminant health. Methanolic and hexanoic extracts from various agricultural areas were prepared over a five-month period. By means of HPLC-DAD, vitamin C (ascorbic acid), essential oil (eugenol), tannin (gallic acid), cinnamic acids (caffeic acid, syringic acid, p-coumaric acid, sinapic acid, and ferulic acid), and flavonoids (catechin, rutin, myricetin, quercetin, apigenin, and kaempferol) were detected and quantified. Solvent type, but not cultivation site or sampling time, explained the observed variation in phytochemical profile. Phytochemicals were found in lower concentrations in hexanoic extracts than in methanolic extracts. Catechin and sinapic acid were discovered to be the two most abundant phytochemicals in the methanolic extract of Farang leaf, followed by other phenolic compounds, essential oils, and water-soluble vitamins. Compared with the methanolic extract, the hexanoic extract of Farang leaves was less effective at scavenging oxidation in terms of 1,1-diphenyl-2-picrylhydrazyl (DPPH), nitric oxide, and superoxide, and α-glucosidase inhibitory activity. Hexanoic extract was found to be less protective against oxidative damage in ruminant erythrocytes than methanolic extract in terms of inhibiting hemoglobin oxidation, lipid peroxidation, and hemolysis. According to the findings of this study, the leaves of Farang (P. guajava L.) are a potential source of phytochemical compounds with wellness properties for ruminant production.

Influence of Recycling Agents Addition Methods on Asphalt Mixtures Properties Containing Reclaimed Asphalt Pavement (RAP)

Recycling agents (RAs) are used to restore the physicochemical properties of the aged asphalt binder existing in the reclaimed asphalt pavement (RAP) material. The best location for adding the RAs in the manufacturing process of the asphalt mixtures containing RAP has always been of concern to asphalt mixture researchers. In this study, vegetable, paraffinic and aromatic extract oils were used as RAs. The effect of RA location on the performance properties of the asphalt mixtures containing different percentages of the RAP material was investigated by adding the RAs in three different locations, including in the virgin binder, in the hot RAP material, and in the final mixture. For this aim, the rutting, cracking, and moisture sensitivity of the mixtures containing different RAs at different locations was investigated. The results showed that the best location for adding the RAs is different for various RAs. The best place for adding the paraffinic, aromatic extract, and vegetable oils in terms are in the virgin binder, in the RAP, and the final mixture, respectively. Therefore, using RAs in their appropriate location can improve the mechanical properties of asphalt mixtures containing RAP.

Organic maize farming practices in Nigeria: Drivers and barriers

Organic farming is gaining global recognition in terms of the role it plays in providing safe and healthy food, income, and maintaining a sustainable environment. Despite these aspects , it faces constraints that, if identified, will play a vital role in its development and formulating policy for its sustainability. Creating an effective policy to improve organic farming necessitates identifying the influencing factors in organic farming method selection as well as barriers encountered. This study, therefore, examined the common types of organic maize farming, their determinants, and their challenges in Nigeria. Primary data collected from 480 respondents were analysed with descriptive statistics and multivariate logistic regression. The result revealed that organic manure, compost manure, biocontrol, and cover cropping were used by the farmers to enrich the soil. Farming experience, membership in a farm-based organization, farm distance, education, income, extension contacts, farm size, and cultural compatibility were the influencing factors of different organic farming systems used in maize production. Inadequate organic food accrediting agencies, inability to meet export demand, high cost and scarcity of organic seeds, lack of financial support, poor marketing system, inadequate supporting infrastructure, poor technical know-how, and pest infestation were the most common problems encountered in organic farming. To enhance participation in organic maize farming practices, there is a need to support organic farmers with financial support, accessible organic accreditation centres, training, educational support, and inputs.

Quality of Life in Patients with Diabetic Foot Ulcers: A Cross-sectional Study.

To analyze the associations among and contributions of sociodemographic, clinical, and psychological variables to quality of life (QoL) related to diabetic foot ulcers (DFUs; DFUQoL). The sample comprised 70 patients with DFUs who answered the following questionnaires: the Hospital Anxiety and Depression Scale, Illness Perception Questionnaire-Brief, Diabetic Foot Ulcer-Short Form, Medical Term Recognition test, and a sociodemographic and clinical questionnaire. Pearson and biserial correlation coefficients, hierarchical regressions, and moderation analyses were conducted to study the relationships among variables. The results showed that a large DFU, threatening representations about DFU, and more psychological distress were associated with lower DFUQoL. Also, more psychological distress, more threatening DFU representations, and taking antibiotics contributed to worse DFUQoL. Clinically significant levels of psychological distress moderated the relationship between the DFU extent and negative emotions. This study showed that QoL and its domains were associated with psychological distress and that QoL was more influenced by DFU representations than by a larger-sized wound, emphasizing the importance of psychological interventions in the treatment of patients with DFUs.

Phytochemical Profiles, Antioxidant, Cytotoxic, and Anti-Inflammatory Activities of Traditional Medicinal Plants: Centaurea pichleri subsp. pichleri, Conyza canadensis, and Jasminum fruticans

Centaurea pichleri subsp. pichleri, Conyza canadensis, and Jasminum fruticans are traditionally used plants grown in Turkey. Methanol extracts were obtained from these plants and pharmacological activity studies and phytochemical analyses were carried out. To evaluate the phytochemical composition, spectrophotometric and chromatographic techniques were used. The extracts were evaluated for antioxidant activity by DPPH●, ABTS●+ radical scavenging, and FRAP assays. The cytotoxic effects of the extracts were investigated on DU145 prostate cancer and A549 lung cancer cell lines. The anti-inflammatory effects of extracts were investigated on the NO amount, TNF-α, IFN-γ, and PGE 2 levels in lipopolysaccharide-stimulated Raw 264.7 cells. The richest extract in terms of phenolic compounds (98.19 ± 1.64 mgGAE/gextract) and total flavonoids (21.85 ± 0.64 mgCA/gextract) was identified as C. pichleri subsp. pichleri methanol extract. According to antioxidant activity determinations, the C. pichleri subsp. pichleri extract was found to be the most active extract. Finally, the C. pichleri subsp. pichleri methanol extract was revealed to be the most effective inhibitor of viability in the cytotoxic activity investigation, and the extract with the best anti-inflammatory action. The findings point to C. pichleri subsp. pichleri as a promising source of bioactive compounds in the transition from natural sources to industrial uses, such as new medications, cosmeceuticals, and nutraceuticals.

Sumac (Rhus coriaria) Extract-Loaded Polymeric Nanosheets Efficiently Protect Human Dermal Fibroblasts from Oxidative Stress.

Under healthy physiological conditions, living organisms possess a variety of antioxidant mechanisms to scavenge overproduced reactive oxygen species (ROS). However, under pathological circumstances, endogenous antioxidant systems may not be adequate to eliminate the excessive amount of oxidants, and thus, a continuous exogenous antioxidant income is required. In this regard, sumac (Rhus coriaria) extract is a good candidate for therapeutic applications, because of its high content of antioxidant polyphenolic compounds. In this work, sumac extract-loaded nanosheets (sumac-nanosheet) have been exploited for loading and controlled release of sumac extract, envisioning topical drug delivery applications. Sumac extract has been obtained through the solvent extraction method, and polymeric nanosheets have been thereafter prepared through the spin coating-assisted layer-by-layer deposition of polycaprolactone (PCL), sumac extract, and poly(d,l-lactic acid) (PDLLA). The collected data show a rich content of the sumac extract in terms of polyphenolic compounds, as well as its strong antioxidant properties. Moreover, for the first time in the literature, we demonstrated the possibility of efficiently loading such extract in polymeric nanosheets and the suitability of this nanoplatform as a reactive oxygen species scavenger in human dermal fibroblasts treated with a pro-oxidant insult.

Method and Models of Extraction of Knowledge from Medical Documents

The paper analyzes the problem of extracting knowledge from clinical recommendations presented in the form of semi-structured corpora of text documents in natural language, taking into account their periodic updating. The considered methods of intellectual analysis of the accumulated arrays of medical data make it possible to automate a number of tasks aimed at improving the quality of medical care due to significant decision support in the treatment process. A brief review of well-known publications has been made, highlighting approaches to automating the construction of ontologies and knowledge graphs in the problems of semantic modeling of a problem-oriented text corpus. The structural and functional organization of the system of knowledge extraction and automatic construction of an ontology and a knowledge graph of a problem-oriented corpus for a specific subject area is presented. The main stages of knowledge extraction and dynamic updating of the knowledge graph are considered: named entity extraction, semantic annotation, term and keyword extraction, topic modeling, topic identification, and relationship extraction. The formalized representation of texts was obtained using a pre-trained BERT transformer model. The automatic selection of triplets "object" - "action" - "subject" based on part-of-speech markup of the text corpus was used to construct fragments of the knowledge graph. An experiment was carried out on a corpus of medical texts on a given topic (162 documents of depersonalized case histories of patients of a pediatric center) without preliminary markup in order to test the proposed solution for extracting triplets and constructing a knowledge graph based on them. An analysis of the experimental results confirms the need for a deeper markup of the corpus of text documents to take into account the specifics of medical text documents. For an unmarked corpus of texts, the proposed solution demonstrates satisfactory performance in view of the selection of atomic fragments included in the automatically generated ontology.

EVALUATION OF THE IMPACT OF VARIOUS EXTRACTS OF Swertia chirata ON ANTIMICROBIAL-RESISTANT STRAINS OF PATHOGENS

In several Asian nations, as well as other regions of the world, the plant Swertia chirata is commonly utilized as a herbal remedy. The current study aimed to assess Swertia chirata's impact on a range of antimicrobial-resistant bacteria. To achieve this, the plant's leaves and stems were extracted using ethanol and methanol. Gram-negative bacteria (Escherichia coli) and Gram-positive bacteria (Staphylococcus aureus) were used as test organisms. The agar well diffusion method was utilized to determine the antibacterial activity and calculate the Minimum Inhibitory Concentration (MIC). Using the broth dilution procedure, MIC was determined. Bacterial sp. demonstrated a significant zone of inhibition against all extracts out of all the strains. Methanol and ethanol were employed as controls. The results indicated that the ethanol extract of the stem and leaves was superior to the methanol extract in terms of its ability to the methanol extract

Chinese technical terminology extraction based on DC-value and information entropy

China's technology is developing rapidly, and the number of patent applications has surged. Therefore, there is an urgent need for technical managers and researchers that how to apply computer technology to conduct in-depth mining and analysis of lots of Chinese patent documents to efficiently use patent information, perform technological innovation and avoid R&D risks. Automatic term extraction is the basis of patent mining and analysis, but many existing approaches focus on extracting domain terms in English, which are difficult to extend to Chinese due to the distinctions between Chinese and English languages. At the same time, some common Chinese technical terminology extraction methods focus on the high-frequency characteristics, while technical domain correlation characteristic and the unithood feature of terminology are given less attention. Aiming at these problems, this paper proposes a Chinese technical terminology method based on DC-value and information entropy to achieve automatic extraction of technical terminology in Chinese patents. The empirical results show that the presented algorithm can effectively extract the technical terminology in Chinese patent literatures and has a better performance than the C-value method, the log-likelihood ratio method and the mutual information method, which has theoretical significance and practical application value.

Open-set recognition of breast cancer treatments

Open-set recognition generalizes a classification task by classifying test samples as one of the known classes from training or “unknown.” As novel cancer drug cocktails with improved treatment are continually discovered, classifying patients by treatments can naturally be formulated in terms of an open-set recognition problem. Drawbacks, due to modeling unknown samples during training, arise from straightforward implementations of prior work in healthcare open-set learning. Accordingly, we reframe the problem methodology and apply a recent Gaussian mixture variational autoencoder model, which achieves state-of-the-art results for image datasets, to breast cancer patient data. Not only do we obtain more accurate and robust classification results (14% average F1 increase compared to recent methods), but we also reexamine open-set recognition in terms of deployability to a clinical setting.

Evaluation of end-to-end aspect-based sentiment analysis methods employing novel benchmark dataset for aspect, and opinion review analysis

Aspect-based sentiment analysis (ABSA) deals with the determination of sentiments for opinion targets. While historically this research task has been addressed with pipeline approaches, more recent works use neural networks to jointly deal with the aspect term and opinion term extraction, as well as the polarity classification. Although learned together, most NN-based approaches and all pipeline approaches do not model correlations between the tasks. This is also based on the absence of adequate datasets which are annotated for all sub-tasks in a unified tagging scheme. We address this bottleneck and introduce the first purposely designed and annotated dataset for ABSA. The DAORA dataset covers 2,100 Tripadvisor reviews, and it is annotated on aspect terms, opinion terms, as well as aspect term polarity, using a unified tagging scheme. It was designed especially for end-to-end aspect-based sentiment analysis of real-world reviews and does not use any sentence repetition or removal. We evaluate the DAORA dataset in several experiments employing state-of-the-art models for ABSA. We set benchmarks and analyze the strengths as well as weaknesses of the data and approaches.

La possible contribution du pharmacien d’officine en amont de la prescription médicamenteuse en France : une expérimentation de groupes de pratique médecins généralistes – pharmaciens d’officine

The implementation of practice groups between general practitioners and community pharmacists in several European countries (Belgium, the Netherlands, Switzerland) emphasizes the possible and relevant role of the community pharmacist upstream of drug prescription. In these groups, the pharmacist provides knowledge and faciltates pluriprofessional exchanges on prescription practices. This research assesses the potential of implementing these practice groups in France. An experiment was set up in France at 9 sites. Its evaluation was based on the use of questionnaires and semi-structured interviews. The operational feasibility and the adherence of pharmacists to these practice groups were assessed. Our results emphasize that the integration of this practice into the pharmacist's activity is possible but encounters limits, particularly in terms of time investment by the meeting leader pharmacists, regardless of their professional status. The satisfaction of the participating pharmacists with this practice, as well as the previous characteristics of their activity, such as an interprofessional practice already established, are positive factors for the adherence of these professionals to this practice. If these practice groups can represent a potential new activity for the community pharmacist, several conditions could facilitate their implementation: the possibility of animation in pairs, pharmacist-physician, in order to accentuate the interprofessional collaboration while mobilizing the skills of community pharmacists, an evolution of the initial training of community pharmacists in order to strengthen the skills required to facilitate these groups, as well as a financial or professional recognition in terms of continuing education.

Patients with Schizophrenia Showed Worse Cognitive Performance than Bipolar and Major Depressive Disorder in a Sample with Comorbid Substance Use Disorders.

Comorbidity of substance use disorders (SUD) and severe mental illness (SMI) is highly frequent in patients, the most common diagnoses being schizophrenia (SZ), bipolar disorder (BD) and major depressive disorder (MDD). Since comorbidity has its own clinical features, and neurocognitive functioning is not always similar to psychiatric symptoms the present study explores the cognitive performance of patients with dual disorders. A neuropsychological battery of tests was used to assess 120 under treatment male patients, 40 for each group considered (SZ + SUD, BD + SUD and MDD + SUD) who were mainly polyconsumers. Significant differences (with premorbid IQ as a covariate) were found among the groups, with SZ + SUD having a worse performance in attention, verbal learning, short term memory and recognition. The consideration of a global Z score for performance evidenced an impaired neurocognitive pattern for SZ + SUD compared with BD + SUD and MDD + SUD. According to norms, all patients showed difficulties in verbal learning, short-term memory and recognition. Our research indicated that the neurocognitive functioning of dual disorder patients was influenced by the comorbid SMI, with SZ + SUD presenting major difficulties. Future studies should thoroughly explore the role of such difficulties as indicators or endophenotypes for dual schizophrenia disorders, and their usefulness for prevention and treatment.

Research on the Application of Multi-Source Information Fusion in Multiple Gait Pattern Transition Recognition.

Multi-source information fusion technology is a kind of information processing technology which comprehensively processes and utilizes multi-source uncertain information. It is an effective scheme to solve complex pattern recognition and improve classification performance. This study aims to improve the accuracy and robustness of exoskeleton gait pattern transition recognition in complex environments. Based on the theory of multi-source information fusion, this paper explored a multi-source information fusion model for exoskeleton gait pattern transition recognition in terms of two aspects of multi-source information fusion strategy and multi-classifier fusion. For eight common gait pattern transitions (between level and stair walking and between level and ramp walking), we proposed a hybrid fusion strategy of multi-source information at the feature level and decision level. We first selected an optimal feature subset through correlation feature extraction and feature selection algorithm, followed by the feature fusion through the classifier. We then studied the construction of a multi-classifier fusion model with a focus on the selection of base classifier and multi-classifier fusion algorithm. By analyzing the classification performance and robustness of the multi-classifier fusion model integrating multiple classifier combinations with a number of multi-classifier fusion algorithms, we finally constructed a multi-classifier fusion model based on D-S evidence theory and the combination of three SVM classifiers with different kernel functions (linear, RBF, polynomial). Such multi-source information fusion model improved the anti-interference and fault tolerance of the model through the hybrid fusion strategy of feature level and decision level and had higher accuracy and robustness in the gait pattern transition recognition, whose average recognition accuracy for eight gait pattern transitions reached 99.70%, which increased by 0.15% compared with the highest average recognition accuracy of the single classifier. Moreover, the average recognition accuracy in the absence of different feature data reached 97.47% with good robustness.

Exploration of Extraction and Separation Techniques for Routine Trace Analysis of Organic Compounds in Water: Dispersive Liquid-Liquid Microextraction vs Liquid-Liquid Extraction

Dispersive liquid-liquid microextraction (DLLME) was compared to liquid-liquid extraction (LLE) in terms of the methods’ abilities to analyze samples and ultimately to provide information to an analyst. A simple method of relative quantification by compound class approximation was introduced and its validity tested, while the merits of comprehensive gas chromatography – time-of-flight mass spectrometry (GC×GC-TOFMS) were exhibited on multiple sets of locally obtained environmental water samples. 20 classes of compounds were effectively identified by the DLLME-GC×GC-TOFMS protocol proposed. The limits of detection (LOD) of the protocol ranged between 17 and 377 times lower than the conventional protocol designed for targeted total extractable hydrocarbon (TEH) and total petroleum hydrocarbon (TPH) analysis, with LODs of selected compounds between 0.08 and 1.0 µg/L. Relative quantification shows promising results and was used for quantification of non-targeted analytes within real samples. This quantification method will be used to inform future work to be implemented in industrial environmental analysis.

A Correlational Study on Teachers' Occupational Stress, Job Anxiety, Personality Dimensions and Performance

This study determined the correlations between occupational stress, job anxiety, personality dimensions and instructional competence of elementary teachers. The study employed the descriptive-correlational research design. There were 161 respondents composed of different teachers from small and big schools in the District of Los Banos, Laguna. The study utilized standardized questionnaires to assess the Occupational Stress, Job Anxiety, Personality Dimensions, and Instructional Competence of Elementary Teachers. The data gathered were treated using Mean, Standard Deviation, and ANOVA. The findings revealed that occupational stress has a significant relationship with the teacher's competence in terms of communicative competence. However, occupational stress has no significant relationship between the teacher's competence in terms of instructional competence and social skills. The result also shows that there is a significant relationship between job anxiety in terms of recognition and teacher's competence in terms of instructional competence. However, there is no significant relationship between job anxiety in terms of recognition and teacher's performance in terms of communicative competence and social skills. Similarly, there is a significant relationship between job anxiety in terms of self-esteem and teacher's competence in terms of instructional and communicative competence. However, there is no significant relationship between job anxiety in terms of self-esteem and teacher's competence in terms of social skills. Lastly, the result shows that there is no significant relationship between job anxiety in terms of security, human relations at work, rewards and punishment, future prospects and capacity for work, and teacher's performance in terms of instructional competence, communicative competence, and social skills.