Automated system for calving time prediction and cattle classification utilizing trajectory data and movement features.

Accurately predicting the calving time in cattle is essential for optimizing livestock management and ensuring animal welfare. Our research focuses on developing a robust system for calving cattle classification and calving time prediction, utilizing 12-h trajectory data for 20 cattle. Our system classifies cattle as abnormal (requiring human assistance) or normal (not requiring assistance) and predicts calving times based on their individual behaviors.

Predictive modeling of cattle calving time emphasizing abnormal and normal cases by using posture analysis.

Accurate calving time prediction plays a critical role in ensuring the well-being of both mother and calf during parturition. Challenges during the calving process, particularly in abnormal cases, often necessitate human intervention to prevent potentially fatal outcomes. This study proposes a novel system for automated prediction of normal and abnormal cattle calving cases based on posture analysis.

AI-enhanced real-time cattle identification system through tracking across various environments.

Video-based monitoring is essential nowadays in cattle farm management systems for automated evaluation of cow health, encompassing body condition scores, lameness detection, calving events, and other factors. In order to efficiently monitor the well-being of each individual animal, it is vital to automatically identify them in real time. Although there are various techniques available for cattle identification, a significant number of them depend on radio frequency or visible ear tags, which are prone to being lost or damaged.

Development of a real-time cattle lameness detection system using a single side-view camera.

Recent advancements in machine learning and deep learning have revolutionized various computer vision applications, including object detection, tracking, and classification. This research investigates the application of deep learning for cattle lameness detection in dairy farming. Our study employs image processing techniques and deep learning methods for cattle detection, tracking, and lameness classification.

Revolutionizing Cow Welfare Monitoring: A Novel Top-View Perspective with Depth Camera-Based Lameness Classification.

This study innovates livestock health management, utilizing a top-view depth camera for accurate cow lameness detection, classification, and precise segmentation through integration with a 3D depth camera and deep learning, distinguishing it from 2D systems. It underscores the importance of early lameness detection in cattle and focuses on extracting depth data from the cow's body, with a specific emphasis on the back region's maximum value. Precise cow detection and tracking are achieved through the Detectron2 framework and Intersection Over Union (IOU) techniques.

Customized Tracking Algorithm for Robust Cattle Detection and Tracking in Occlusion Environments.

Ensuring precise calving time prediction necessitates the adoption of an automatic and precisely accurate cattle tracking system. Nowadays, cattle tracking can be challenging due to the complexity of their environment and the potential for missed or false detections. Most existing deep-learning tracking algorithms face challenges when dealing with track-ID switch cases caused by cattle occlusion.

Five-year species distribution and antimicrobial susceptibility of non-tuberculous mycobacteria in Malaysia, 2018-2022.

Non-tuberculous Mycobacteria (NTM) is a group of mycobacteria distinct from the Mycobacterium tuberculosis complex. They can cause opportunistic infections, especially in immunocompromised individuals. Over the last few years, there has been a growing concern regarding the distribution and antimicrobial resistance of NTM in Malaysia.

A Markov Chain Model for Determining the Optimal Time to Move Pregnant Cows to Individual Calving Pens.

The use of individual calving pens in modern farming is widely recognized as a good practice for promoting good animal welfare during parturition. However, determining the optimal time to move a pregnant cow to a calving pen can be a management challenge. Moving cows too early may result in prolonged occupancy of the pen, while moving them too late may increase the risk of calving complications and production-related diseases.

Cow detection and tracking system utilizing multi-feature tracking algorithm.

In modern cattle farm management systems, video-based monitoring has become important in analyzing the high-level behavior of cattle for monitoring their health and predicting calving for providing timely assistance. Conventionally, sensors have been used for detecting and tracking their activities. As the body-attached sensors cause stress, video cameras can be used as an alternative.

The association between exon3 gene variants and keratoconus in Malaysian patients.

Purpose: This case-control study aims to examine possible associations of VSX1 exon3 gene variants with the development of keratoconus (KC) in Malaysian patients.

Methods: A case-control study was done on 42 keratoconus cases, 127 family member controls, and 96 normal controls.

Results: Three gene variants, p.

Socio-economic and agricultural factors associated with stunting of under 5-year children: findings from surveys in mountains, dry zone and delta regions of rural Myanmar (2016-2017).

Objective: The study's objective was to investigate multiple underlying social, economic and agricultural determinants of stunting among under-five children in three distinct ecological areas in rural Myanmar.

Design: Repeated cross-sectional surveys in three states of Myanmar.

Setting: Rural households in Chin (mountainous), Magway (plains) and Ayeyarwady (delta).

Mutations in may confer resistance to gentamicin in .

Listeriosis, a foodborne infection caused by , could lead to febrile listerial gastroenteritis and a more invasive form which is often associated with a high mortality and hospitalisation rate. Gentamicin, used as an adjunct therapy with ampicillin, remains the treatment of choice for this life-threatening and invasive infection. Nevertheless, there is little data on gentamicin resistance determinants in .

Incidence of cutaneous graft-versus-host disease in a Singapore academic medical centre - A retrospective cohort study.

Background: Cutaneous graft-versus-host disease (GVHD) is common in allogeneic haematopoietic stem cell transplantation. HLA mismatch is the most significant determinant of GVHD. Our study aimed to compare the incidence of cutaneous GVHD haploidentical (Haplo) and matched donors in an Asian population.

Comparing State-of-the-Art Deep Learning Algorithms for the Automated Detection and Tracking of Black Cattle.

Effective livestock management is critical for cattle farms in today's competitive era of smart modern farming. To ensure farm management solutions are efficient, affordable, and scalable, the manual identification and detection of cattle are not feasible in today's farming systems. Fortunately, automatic tracking and identification systems have greatly improved in recent years.

HMM-Based Action Recognition System for Elderly Healthcare by Colorizing Depth Map.

Addressing the problems facing the elderly, whether living independently or in managed care facilities, is considered one of the most important applications for action recognition research. However, existing systems are not ready for automation, or for effective use in continuous operation. Therefore, we have developed theoretical and practical foundations for a new real-time action recognition system.

RshA mutations contributing to tigecycline resistance in .

Tigecycline is an important rescue antibiotic for many bacterial infections. In , tigecycline resistance has been associated with dysregulated stress response caused by aberrations in the interaction of the SigH and RshA factors. In this study, two tigecycline-resistant mutants of (CL5A and CL6A) with mutations in the gene were studied using gene complementation, RT-qPCR and the bacterial adenylate cyclase two-hybrid (BACTH) system.

An Absorbing Markov Chain Model to Predict Dairy Cow Calving Time.

Abnormal behavioral changes in the regular daily mobility routine of a pregnant dairy cow can be an indicator or early sign to recognize when a calving event is imminent. Image processing technology and statistical approaches can be effectively used to achieve a more accurate result in predicting the time of calving. We hypothesize that data collected using a 360-degree camera to monitor cows before and during calving can be used to establish the daily activities of individual pregnant cows and to detect changes in their routine.

Real-Time Action Recognition System for Elderly People Using Stereo Depth Camera.

Smart technologies are necessary for ambient assisted living (AAL) to help family members, caregivers, and health-care professionals in providing care for elderly people independently. Among these technologies, the current work is proposed as a computer vision-based solution that can monitor the elderly by recognizing actions using a stereo depth camera. In this work, we introduce a system that fuses together feature extraction methods from previous works in a novel combination of action recognition.

Effect of syringin (eleutheroside B) on the physiological and hematological parameters in STZ induced Type II diabetic Wistar rats.

To investigate the physiological indices such as body weight, food and fluid drinking concern to antidiabetic properties of syringin and its useful outcome on hematological parameters in streptozotocin stimulated diabetic rats. Six normal and 18 diabetic rats totally 24 rats have been used for the present investigation. Streptozotocin was injected in male Wistar rats to induce diabetes through intraperitoneal route.

Patient safety and public health concerns: poor dissolution rate of pioglitazone tablets obtained from China, Myanmar and internet sites.

Background: Poor quality medicines have serious implications for public health. The aim of this study was to explore the quality of the antidiabetic pioglitazone, using samples collected in China and Myanmar, and samples purchased online.

Methods: In this cross-sectional study, we examined samples (n = 163) collected from hospitals in Shanghai, China in 2012 (n = 44), products purchased via the internet and imported into Japan in 2013 (n = 59), and samples purchased in shops in Yangon, Myanmar in 2015 (n = 60).

Activity-Integrated Hidden Markov Model to Predict Calving Time.

Accurately predicting when calving will occur can provide great value in managing a dairy farm since it provides personnel with the ability to determine whether assistance is necessary. Not providing such assistance when necessary could prolong the calving process, negatively affecting the health of both mother cow and calf. Such prolongation could lead to multiple illnesses.

Performance of Malaria Volunteers regarding Malaria Control Activities in Southeastern Myanmar: A Study in the Areas under Coverage of an Ethnic Health Organization.

Malaria volunteers (MVs) play an essential role in resolving malaria problems by delivering greater access to diagnosis and treatment services, mainly for the underserved community residing in hard-to-reach rural areas. The Karen Department of Health and Welfare (KDHW) has implemented community-based malaria control activities among the ethnic minorities in southeastern Myanmar by promoting the roles of MVs. This study aimed to explore the factors influencing the performance of MVs regarding malaria control activities in the area.

Antidiabetic potential and high synergistic antibacterial activity of silver nanoparticles synthesised with Musa Paradisiaca tepal extract.

This work investigates the Musa Paradisiaca plant and its tepal extracts. The research findings show that the tepal extracts of M. Paradisiaca contain high phytochemical activity.