Financial Losses Research Articles

Machine Learning and Wavelet Transform: A Hybrid Approach to Predicting Ammonia Levels in Poultry Farms.

Ammonia (NH3) is a major pollutant in poultry farms, negatively impacting bird health and welfare. High NH3 levels can cause poor weight gain, inefficient feed conversion, reduced viability, and financial losses in the poultry industry. Therefore, accurate estimation of NH3 concentration is crucial for environmental protection and human and animal health. Three widely used machine learning (ML) algorithms-extreme learning machine (ELM), k-nearest neighbor (KNN), and random forest (RF)-were initially used as base algorithms. The wavelet transform (WT) with ten levels of decomposition was then applied as a preprocessing method. Three statistical metrics, including the mean absolute error (MAE) and the correlation coefficient (R), were used to evaluate the predictive accuracies of algorithms. The results indicate that the RF algorithms perform robustly individually and in combination with the WT. The RF-WT algorithm performed best using the air temperature, relative humidity, and air velocity inputs with a MAE of 0.548 ppm and an R of 0.976 for the testing dataset. In summary, applying WT to the inputs significantly improved the predictive power of the ML algorithms, especially for inputs that initially had a low correlation with the NH3 values.

Innovation and possibility of various coating materials with microwave hybrid heating

Cavitation wear is causing considerable financial losses for a range of industries, such as chemical, food processing and hydropower plants. Microwave cladding process involves the application of a coating of another material over the surface of a specific material, which offers properties beneficial for high electrical conductivity, low loss tangent and excellent thermal stability. This review article is intended to provide a basic understanding of the properties of various types of microwave cladding materials. This chapter also emphasises on the characterisation of the samples produced through the microwave cladding on various substrate materials. Furthermore, this chapter describes the potential applications of the microwave cladding process in numerous engineering and industrial sectors. Additionally, this chapter also reports the potential future technological advancements in the field of microwave cladding process.

Pipeline Leak Identification and Prediction of Urban Water Supply Network System with Deep Learning Artificial Neural Network

Pipeline leakage, which leads to water wastage, financial losses, and contamination, is a significant challenge in urban water supply networks. Leak detection and prediction is urgent to secure the safety of the water supply system. Relaying on deep learning artificial neural networks and a specific optimization algorithm, an intelligential detection approach in identifying the pipeline leaks is proposed. A hydraulic model is initially constructed on the simplified Net2 benchmark pipe network. The District Metering Area (DMA) algorithm and the Cuckoo Search (CS) algorithm are integrated as the DMA-CS algorithm, which is employed for the hydraulic model optimization. Attributing to the suspected leak area identification and the exact leak location, the DMA-CS algorithm possess higher accuracy for pipeline leakage (97.43%) than that of the DMA algorithm (92.67%). The identification pattern of leakage nodes is correlated to the maximum number of leakage points set with the participation of the DMA-CS algorithm, which provide a more accurate pathway for identifying and predicting the specific pipeline leaks.

Surveillance on antimicrobial Resistance pattern of Third Generation Cephalosporins at the Benjamin Mkapa Tertiary Hospital in Tanzania

Abstract Background Antimicrobial resistance is a burden in Tanzania and the world economy, resulting in financial losses from lower production brought on by illness due to greater treatment expenses and death. Second- and third-line antibiotics like third generations of cephalosporins should be used rather than first-line, which is an expensive option, due to AMR. The direct effects of AMR include severe prolonged illnesses, prolonged hospital stays death, and (Global Action Plan on Antimicrobial Resistance., 2015) Methodology The retrospective study design was used to review AST to assess the AMR patterns from 2020-2022 for urine, pus, and blood samples as stated in the National Action Plan-Antimicrobial Resistance 2017. Results Three years (2020, 2021, and 2022) of antibiograms based on priority samples, priority pathogens and third generations of cephalosporins for both gram-negative and gram-positive bacteria see Tables 1 and 2. The surveillance identified sensitive (S), intermediate(I), and resistance(R) for tested bacteria. The N is the isolate number. Our antibiograms for third-generation cephalosporins were represented by cefotaxime, ceftazidime and ceftriaxone. The antimicrobial resistance to ceftriaxone for Acinetobacter species was 62.5% while 76% for Citrobacter. E. coli at 60.26%, Enterobacter aerogenes at 67.86%, Klebsiella species at 73.48% at 22.73%, Morganella morganii 65.75% and Staphylococcus aureus at 62.5%, Serratia marcescens 64.56%. Similar resistance trends have been observed in cefotaxime and ceftazidime. Conclusion Antimicrobial susceptibility surveillance, antimicrobial rotation and presentation of findings to clinicians for increased awareness and the promotion of a multi-disciplinary approach to successful AMS programmers is essential. Evidence found will optimize the use of antibiotics. Clinicians, pharmacists, and scientists will use obtained evidence in the development of guidelines and protocols for surgical prophylaxis, setting IPC programs, management of bacterial blood infections (septicemia and sepsis) and managing urinary tract infections by focusing on red flags antibiotics and bacteria such E. coli and K. pneumoniae. Avoiding delay of AST results by enough resources, and technology advancement. This enable identification of the causative pathogens facilitated the correct diagnosis, de-escalation, and use of targeted agents, which are necessary to promote the prudent use of antimicrobials. Antibiograms Table 1: Antibiogram of gram-negative bacteria Table 2: Antibiogram of gram-positive bacteria

Psychosocial and pandemic-related circumstances of suicide deaths in 2020: Evidence from the National Violent Death Reporting System.

To describe and explore variation in 'pandemic-related circumstances' among suicide decedents during the first year of the COVID-19 pandemic. We identified pandemic-related circumstances using decedents' text narratives in the 2020 National Violent Death Reporting System. We use time-series analysis to compare other psychosocial characteristics (e.g., mental health history, interpersonal difficulties, financial strain) of decedents pre-pandemic (2017/2018: n = 56,968 suicide and n = 7,551 undetermined deaths) to those in 2020 (n = 31,887 suicide and n = 4,100 undetermined). We characterize common themes in the narratives with pandemic-related circumstances using topic modeling, and explore variation in topics by age and other psychosocial circumstances. In 2020, n = 2,502 (6.98%) narratives described pandemic-related circumstances. Compared to other deaths in 2020 and to the pre-pandemic period, decedents with pandemic-related circumstances were older and more highly educated. Common themes of pandemic-related circumstances narratives included: concerns about shutdown restrictions, financial losses, and infection risk. Relative to decedents of the same age that did not have pandemic-related circumstances in 2020, those with pandemic-related circumstances were more likely to also have financial (e.g., for 25-44 years, 43% vs. 12%) and mental health (76% vs. 66%) psychosocial circumstances, but had similar or lower prevalence of substance abuse (47% vs. 49%) and interpersonal (40% vs. 42%) circumstances. While descriptive, these findings help contextualize suicide mortality during the acute phase of the COVID-19 pandemic and can inform mental health promotion efforts during similar public health emergencies.

Performance of different rice genotypes cultivated under submergence and normal growing conditions

Abstract Submergence negatively affects the plant growth and yield of rice genotypes, which in turn results in huge financial loss. Thus, identification of submergence tolerance rice genotypes is needed for sustainable rice cultivation in flood-prone areas. Keeping this in view, a two-year (2019 and 2020) field study was undertaken at Rice Research Farm of Bihar Agricultural College, Bihar Agricultural University, Sabour, Bhagalpur to investigate and compare the yield responses of rice genotypes under submergence and normal growing conditions. Twenty-five days old seedlings of 25 rice genotypes were transplanted in a randomized complete block design in two replicates, which were allowed to grow under normal practice for the next 25 days. Thereafter, the 50-day old plants were completely submerged with turbid water of 1.5 m height for the next 18 days. After de-submergence, all the recommended agronomic practices were adopted during the rest of the crop period. Under submergence, higher grain yield was recorded under all the genotypes during 2020 as compared to 2019 mainly due to higher temperature and lesser rainfall during 2020. Under submergence conditions, Jalmagna, Nona Bokra and Swarna Sub 1 were the best performers having produced average yields of 3,167, 2,786 and 2,741 kg/ha, respectively. Whereas under normal growing practice, Swarna Sub 1, Jalmagna and Sudha were the first three best performing genotypes producing average yields of 5,063, 4,565 and 4,456 kg/ha, respectively. Therefore, Jalmagna should be preferred for cultivation in the flood-prone regions of the state, however in non-flooded areas; Swarna Sub 1 may be cultivated.

Impact Of Global Semiconductor Shortage on The Domestic New Energy Vehicle Supply Chain in Australia And Measures to Mitigate Such Risks in The Future

Different industries have been affected by the shortage of semiconductors globally, and one of the most affected industries is the New Energy Vehicle (NEV) industry within Australia. Semiconductors play a massive role in NEV features like battery management and power management. These factors include the COVID-19 pandemic, the rise in electronics demand, natural calamities, and most importantly the shortage which has affected NEV production and sales in Australia. This paper discusses the consequences of the lack of supply of such components on the Australian NEV supply chain: They stop production, low inventory levels, financial losses, and slowed innovation. It brings out vulnerability issues including dependence on limited suppliers from Asia and the absence of chip-making factories within North America. Based on the identified threats, the paper outlines the following solutions: supplier diversification, increasing inventory levels, raising supply chain visibility, investing in domestic semiconductor production, incentives for buyers, and sourcing non-semiconductor material technologies. Such measures are strategic and intended to secure an NEV supply chain in Australia that is both sustainable and environmentally friendly.

A Pilot Study Examining The Efficacy Of Occupational Therapy Rehabilitation Programmes For Students With Work-Related Muscular-Skeletal Disorders

Background: Musculoskeletal issues at work have an influence on daily life, productivity, and quality of life. Musculoskeletal issues that go untreated can result in severe damage and function loss, which can limit participation, cause financial loss, and add to the rising burden of illness in the world. Objective: The purpose of this study was to find the effect of occupational therapy rehabilitation program in occupational therapy students with work related musculoskeletal disorder. Study Design:Quasi-experimental, pilot study design was chosen for the research Methods: The study employed a quasi-experimental study design. Thirty occupational therapy students aged 20-25 years were recruited through convenience sampling after a prevalence check where 30 students reported 54 musculoskeletal problems. A total number of participants (n= 30) received occupational therapy rehabilitation program. Standardised Nordic musculoskeletal questionnaire (SNMQ) and Numeric pain rating scale (NPRS) were administered to Pain and work related musculoskeletal disorder for all the participants. Result: It revealed that there was a statistically significant difference in pre-test and post-test with numeric pain rating scale (t=10.625, p=0.000). There was a significant difference in percentage in 7 days component of SNMQ. There was no statistical difference with post-test of score of 12 months component of SNMQ. Conclusion: Occupational therapy rehabilitation program is effective for reducing Musculoskeletal disorder or discomfort in occupational therapy students.

Enhancing physio-biochemical characteristics in okra genotypes through seed priming with biogenic zinc oxide nanoparticles synthesized from halophytic plant extracts

Poor seedling germination and growth can result in large financial losses for farmers, thus, there is an urgent need for sustainable agricultural techniques to enhance seed germination and early growth. As an outcome, sustainable agriculture-which emphasizes the smart and effective utilization of resources-has gained popularity worldwide. At numerous levels, the field of nanotechnology is capable of significant benefit in achieving sustainable agricultural practices. Zinc oxide nanoparticles (ZnO NPs) have been shown to have biostimulatory properties and serve as effective solutions for addressing environmental and biotic stressors. The purpose of this study, investigating Salvadora persica halophytic leaf extract -synthesized zinc oxide nanoparticles (S-ZnONPs) as nano-priming agents to ensure okra seeds germinated under stress-free conditions. From an application perspective, we examined the effect of seed priming with varying concentrations of S-ZnO NPs (0, 20 and 40 ppm) for 18 and 24 h of soaking. Results indicated that the germination rate of hybrid variety improved with 20 ppm at 18 h, increasing by 58.22%, while mean germination time reduced by 24.62%. An enhancement trend was observed in the shoot, root length, shoot and root fresh weight, shoot and root dry weight of hybrid variety at 20ppm with 18 h priming by 34.2, 84.3, 80.2, 47.4, 50.3, and 36.2%, respectively. However, chlorophyll pigments chl a, chl b, and carotenoids was significantly raised in desi variety by 42.4, 79.31, and 142.29% with 20 ppm at 18 h priming. Hydrogen per oxide decreased up to 87.8% with 40 ppm at 24 h in hybrid variety, while, in desi variety H2O2 was reduced 88.3% with 20 ppm at 24 h. Non enzymatic antioxidant activities such as ascorbic acid, was highly increased 130.6% in hybrid at 24 h priming with 20 ppm dose. Flavonoids raised in same variety by 166.1% with 20 ppm at 18 h. Proline content was increased by 144.5% with 40ppm at 18 h. Moreover, Antioxidant enzymes, superoxide dismutase, peroxidase and catalase were significantly increased in both varieties with both levels of S-ZnO NPs and priming time. This cost-effective and environmentally safe technique to produce nanoparticles of different halophytic plants can maximize resource utilization, supporting sustainable agriculture by minimizing adverse environmental effects without compromising efficiency.

Classifying adaxial and abaxial sides of diseased citrus leaves with selected hyperspectral bands and YOLOv8

Huanglongbing (HLB; citrus greening) and citrus canker are invasive diseases afflicting Florida citrus groves, causing financial losses through yield loss, smaller fruit, blemishes, premature fruit drop and/or eventual tree death. Often, symptoms of these diseases resemble those of other disease or disorders. Early detection of HLB and canker via in-grove leaf inspection can permit more effective mitigation tactics and management of groves. Autonomous, vision-based disease scouting in a grove offers a financial benefit to the Florida citrus industry. This study investigates the potential of hyperspectral reflectance imagery (HSI) for detecting and classifying these conditions in the presence of other, less consequential leaf defects. Leaves with visible symptoms of HLB, canker, zinc deficiency, scab, melanose, greasy spot, and a control set were collected and both sides were imaged with a line-scan hyperspectral camera. Spectral bands from this imagery were selected using two methods: an unsupervised method based on principal component analysis (PCA), a supervised method based on linear discriminant analysis (LDA), which were compared with randomly selected bands as a control. The YOLOv8 network architecture was trained to classify each side of these leaves with each band combination. LDA-selected bands from the front of the leaves yielded an overall classification accuracy of 87.09 %, with higher recall of melanose and precision of control than any other model tested. Leaves with HLB and zinc deficiency were classified most accurately, with both band selection methods yielding F1 scores of at least 0.955 and 0.934, respectively. These findings favor the use of supervised band selection for HSI-based in-grove disease detection.

Mapping pathogenic fungi in decayed Norway spruce stands: Insights from harvester positional data

Abstract Root and butt rot caused by pathogenic fungi in the genera Heterobasidion and Armillaria is a pressing issue in managed Norway spruce forests. The disease results in financial losses for the forest owners and reduces the volume of wood that can be used in long‐lived products. Pathogenic wood decay fungi spread either with the aid of airborne spores or via mycelial growth among neighbouring trees, the latter leading to clustering (tendency of decayed trees to be in close proximity relative to their neighbouring trees) of decay‐affected trees in forests. Understanding the spatial patterns of the decay‐affected trees at the forest stand level is vital for designing management strategies to address this problem. We examined decay clustering in 273 clear‐cut Norway spruce stands in Norway using harvester‐recorded data on spatial occurrence of decayed and healthy Norway spruce trees. We tested clustering using three global‐cluster tests that account for population density and distribution, evaluating clustering without identifying specific cluster locations. The proportions of clustered and non‐clustered stands differed depending on the statistical test used for clustering assessment, resulting in overall agreement of 32.8% for clustered and 36.9% for non‐clustered. Clustered stands exhibited a median cluster distance (maximum distance between the decay‐affected trees within a cluster) of 12 m (Inter‐Quantile Range, IQR, 6–20 m) and a median of 6 (IQR 3–16) nearest neighbour trees (number of decayed trees forming a cluster), estimates comparable with prior studies focused on assessment of trees infected by mycelial spread of the same fungal individual. The decay incidence in the clustered stands was 16.24%, while the non‐clustered stands had a butt‐rot incidence of 20.97%. In clustered stands the average number of trees per hectare was higher (693) than in non‐clustered stands (553). Synthesis and applications: Our study demonstrates that Norway spruce stands display a diverse range of spatial patterns of butt rotted trees. We found that higher densities of Norway spruce trees probably facilitate the vegetative spread of pathogenic wood decay fungi, leading to clustering of decay‐affected trees. To disrupt the spread of decay fungi between tree generations, precision planting of trees other than Norway spruce around infested stumps of prior generation trees has been recommended by earlier studies. We discussed the potential of using harvester‐derived geoposition data for butt‐rotted trees upon planning and execution of forest regeneration.

Empowering Communities to Reduce Dependence on Unlicensed Mining and Minimize Corporate Losses: A Case Study of PTBA in December 2023

This study aims to analyze the impact of community empowerment programs on reducing dependence on unlicensed mining and to measure the potential losses incurred by PTBA due to these activities. The time sample used in this research is December 2023. A quantitative approach is used to calculate the income earned by the community from six empowerment programs, including bamboo downstream processing, snakehead fish farming, reclamation plant cultivation, maggot farming, quail farming, and eel farming. The total income generated by these programs for 93 beneficiaries reached USD 13,238.22 per month, with an average income per program ranging from USD 153.70 to USD 244.39, which remains below the regional minimum wage (UMR) of Muara Enim Regency, set at USD 233 per month. This income is compared to assess how competitive the alternative livelihoods provided by the empowerment programs are. In addition, this study calculates PTBA’s losses from unlicensed mining in the same month, based on the extraction of 0.175 million tons of coal, the market price of USD 58.28 per ton, and the lost royalties of 8%. The total financial loss reached USD 10.2 million, with USD 815,920 in lost royalties. The analysis underscores the importance of expanding and strengthening community empowerment programs to further reduce unlicensed mining activities, while also mitigating the financial and environmental impacts on the company.

Enhancing dehydration/desalting efficiency of crude oil emulsions through experimental and computational insights

The formation of unwanted oil emulsions during producing, transporting, and processing crude oils is a major challenging issue, which causes serious technical problems, and subsequently huge financial losses. The present work delves into an optimization study focused on water separation from crude oil emulsions. The separation performance was initially assessed in static conditions through bottle tests, followed by a thorough investigation in dynamic conditions on an electrostatic desalting pilot plant under various conditions of the main operating parameters: temperature, oil space velocity, wash water ratio, and demulsifier concentration. The design of experiments and optimization of the process were performed by Central-Composite-Design of Response-Surface-Methodology (CCD-RSM). The effectiveness of the separation process has been analyzed by evaluating the Water-Removal-Efficiency (WRE) and Salt-Removal-Efficiency (SRE). The obtained results demonstrated that the used demulsifier was found to be extremely efficient and to have the greatest impact on the dehydration efficiency (F-value = 434.56). In addition, the sensitivity analysis indicated that the dehydration/desalting process is also very sensitive to the oil space velocity and wash water ratio while having less sensitivity to changes in the temperature. Furthermore, the process optimization indicated that the highest efficiency of simultaneous removal of water and salt from crude oil (WRE = 94.54 % and SRE = 97.23 %) was observed at optimal conditions of 19.5 ppm demulsifier concentration, 125 °C temperature, 1 1/h oil space velocity, and 6 vol% wash water ratio.

Fear of Death and Sleep Quality in the Aftermath of an Earthquake.

To examine fear of death and disruption in sleep patterns in individuals who have experienced an earthquake. A descriptive and relationship-oriented study was performed with 322 individuals who experienced the February 6, 2023, earthquake in Turkey. Data were collected between February 20 and May 15, 2023. A personal information form, the Pittsburgh Sleep Quality Index (PSQI), and Death Anxiety Scale (DAS) were used for data collection. Participants' mean DAS score was 7.96 (SD = 1.05), and mean PSQI score was 8.74 (SD = 4.06). Statistically significant relationships were found between sex, marital status, and mean DAS score, and these variables accounted for 11.7% of the total variance. Similarly, statistically significant relationships were found among economic status, relationship to person trapped under the rubble, financial loss from the earthquake, and mean PSQI score, accounting for 11.3% of the total variance. Women and married people had greater fear of death, and those with good economic status, whose family members were buried under rubble, and who experienced financial loss as a result of the earthquake had lower sleep quality. The earthquake led to moderate fear of death and poor sleep quality among participants. Findings highlight the need for targeted support for vulnerable groups following disasters. [Journal of Psychosocial Nursing and Mental Health Services, xx(xx), xx-xx.].

The Development of a Family Support Program for Caregivers of Hemodialysis Patients

Family caregivers of hemodialysis patients have a heavy burden based on negative experiences, long-term care hours, total physical dependence of patients, comorbid health conditions, and financial stress treatment procedures. This study design is a mixed method followed by 114 participants in the quantitative phase and eight participants in the qualitative phase. The research instrument used Zarit Burden, a demographic profile form, semi-structured interview questions, and a recorder. Data analysis used ANOVA, t-test, and thematic analysis. The results showed that most participants were 51 to 60 years old, patients' wives, college graduates, had a monthly income below ph10,000.00 and had cared for patients for 20 to 24 hours. Participants have experienced high physical and financial burdens and loss of control over life, as well as very high emotional and social burdens. Significant differences were found in the levels of emotional, social, and financial burdens when grouped by education level. Monthly income affects the level of social and financial burdens. Physical exhaustion, emotional suffering, limited social life, role conflict, financial poverty, and fear of the future are the themes of challenges in caregiving. Participants coped with their challenges by seeking help and sleep, emotional adjustment, acceptance, maintaining friendships, resisting the urge to participate in social activities, utilizing family resources, seeking financial support from politicians and government agencies, and borrowing money. The proposed stress relief support program has the potential to be an intervention to enable family care with various forms and levels of caregiving burden.

A Comparative Study of Machine Learning Models for Predicting Customer Churn in Retail Banking: Insights from Logistic Regression, Random Forest, GBM, and SVM

Customer churn poses a significant challenge in the retail banking sector, leading to substantial financial losses and undermining long-term growth. This study explores the effectiveness of various machine learning models, including Logistic Regression, Random Forest, Gradient Boosting Machine (GBM), and Support Vector Machine (SVM), in predicting customer churn. Utilizing a comprehensive dataset derived from a leading bank, we conducted extensive data preprocessing and feature engineering before evaluating model performance through metrics such as accuracy, precision, recall, F1-score, and AUC-ROC. Our findings reveal that the Gradient Boosting Machine outperforms its counterparts, achieving an accuracy of 87.2%, with an AUC-ROC score of 0.91, indicating its exceptional ability to distinguish between churned and non-churned customers. Random Forest follows closely, exhibiting robust performance, while SVM and Logistic Regression demonstrate moderate accuracy levels. This research underscores the transformative potential of machine learning in enhancing customer retention strategies within the banking industry. By identifying at-risk customers and understanding the underlying factors contributing to churn, banks can implement targeted interventions to improve customer satisfaction and loyalty. The study further suggests avenues for future research, including the exploration of real-time data analysis and the integration of qualitative customer insights, to refine predictive models and retention strategies.

Multicentric Study on Enteric Protists Occurrence in Zoological Parks in Portugal.

Parasitic infections of the gastrointestinal tract of domestic animals play a major role in the transmission of disease, which in turn may result in financial and productive losses. Notwithstanding, studies on the burden and distribution of diarrheagenic protists in zoological gardens are still insufficient. Given the close animal-animal and animal-human interaction in these settings, Public Health concerns under the One Health context are raised. Using molecular detection tools and phylogenetic analysis, the goal of this study was to assess the occurrence of four potentially zoonotic protists-Balantioides coli, Blastocystis sp., Cryptosporidium spp. and Giardia spp.-in animals residing in zoological parks in Portugal. Occurrence of Eimeria spp. was also assessed because of its veterinary relevance. Although Blastocystis sp. represents most of the positive samples obtained (11.6%; 95% CI: 0.08-0.17), all parasites were detected (B. coli (2.9%; 95% CI: 0.01-0.06), and Cryptosporidium spp., Eimeria spp. and Giardia spp. presented the same prevalence (0.5%; 95% CI: 0.00-0.03)). We also describe the first molecular detection of B. coli in a collared peccary (Tayassu tajacu), of Blastocystis sp. in three different python species, and G. muris in a central bearded dragon (Pogona vitticeps), suggesting the broadening of the host range for these parasites.

The Immune Defense Response and Immune-Related Genes Expression in Macrobrachium nipponense Infected with Decapod Iridescent Virus 1 (DIV1).

Macrobrachium nipponense is a significant cultivated species in China. However, decapod iridescent virus 1 (DIV1), as a newly discovered crustacean-lethal virus, has resulted in significant financial losses for the M. nipponense industry. In order to examine the immunological response of M. nipponense to DIV1, we conducted transcriptome analysis of the hepatopancreas from M. nipponense infected with DIV1 using RNA-seq. RNA sequencing analysis identified a combined total of 41,712 assembled unigenes, and 7014 genes that showed differential expression were identified in the group infected with DIV1, compared to the control group. Among these DEGs, 3952 were found to be up-regulated, while 3062 were down-regulated; many well-characterized DEGs were involved in innate immune defense, particularly involving the C-type lectin receptor signaling pathway, complement and coagulation cascades, phagosome, lysosome and PPAR signaling pathway. Moreover, the expression levels of well-known immune-related genes (dorsal, wnt6, lectin, caspase, integrin, hsp70) in the hepatopancreas and hemolymph were investigated by Quantitative real-time PCR (qRT-PCR), and the findings demonstrated a significant increase in gene expression in the hepatopancreas and hemolymph at various time points after infection. The results acquired in this study offered further comprehensive understanding of the immunological response of M. nipponense to DIV1 infection.

Serological and molecular survey of Toxoplasma Gondii in aborted livestock fetuses from Northeast Iran

BackgroundToxoplasmosis not only leads to abortion in humans but also in herbivores, which causes significant financial and quality-adjusted life-year losses. The present study aimed to determine the prevalence of toxoplasmosis in aborted fetuses via serological and molecular assays. Moreover, the genotypes of the obtained isolates were detected.MethodsSerological and molecular methods were used to study aborted fetuses from Bojnourd City, North Khorasan Province, Iran, which included 52 ovines and 16 bovines. Nested PCR of the B1 gene was used to detect parasite DNA in brain tissues. The PCR-RFLP method for the GRA6 gene was used to determine the genotype of T. gondii.ResultsOut of 68 aborted fetuses, 16.1% showed the presence of anti-T. gondii IgG. Among these, 11.7% were identified in bovine fetuses and 4.4% in ovine fetuses. Additionally, two (2.94%) samples of ovine tested positive for anti-T. gondii IgM. Our PCR analysis detected parasite DNA in two cases (2.94%) among 11 IgG-positive samples. All obtained isolates belong to type I of T. gondii.ConclusionInfection with Type I of T. gondii during the neonatal period may partly be responsible for abortion and economic losses in livestock farming in our studied region. To understand the molecular epidemiology and genotypes of T. gondii associated with abortion, further evaluation of aborted samples from different geographical locations is necessary.

A Hybrid Method for Identifying Critical Failure Modes in a Ball Mill

The reliability of a ball mill is crucial for the seamless operation of ore processing and other industrial plants, where unexpected equipment failure or downtime can result in significant financial losses and reduced production efficiency. Thus, this paper examined a hybrid method for identifying critical failure modes in a ball mill using the Failure Modes, Effects, and Criticality Analysis combined with the Complex Proportional Assessment with Grey Numbers (COPRAS-G). The COPRAS-G method was employed to assess the criticality of various failure modes by determining the weights of significant failure modes in the bearing, gearbox, motor, and shaft components of a ball mill. It was observed that gear seal failure is the most critical failure with percentage contribution (Ni) of 100%, while bearing wear is the least critical failure with percentage contribution (Ni) of 62%. The result suggests that failure modes of gear seal failure, gear pitting, motor bearing fatigue, and shaft fracture are regarded as the main contributors to failure with percentage contribution (Ni) of 100%, 97%, 87% and 83% respectively. Current ball mill maintenance includes corrective, preventive and predictive maintenance. For failure modes with high criticality, predictive maintenance was advised, while for moderate and low criticality, corrective and preventive maintenance were advised.