Harm to the Well-being of the Udder at the Level of Dairy Farms of Sidi Mhamed Benali Wilaya of Relizane (Algeria)

Background: Among the dairy cattle production problems in Algeria, mastitis rank first in terms of socio-economic impact. Our aim is to identify the state of well-being of the udder in order to manage and control mastitis related problems. Methods: The pH analysis of 177 cow milk samples was performed at two farms located in the Sidi Mhamed Benali region in northwest Algeria associated with an assessment (of the udder’s cleanliness degree, the udder’s position, the teat’s hyperkeratosis lesion and the ITH) out over a period of one year (2020-2021). Result: Analysis of mean (of cleanliness, udder position and ITH) between cold and warm season were significantly different at a value of [(4.11; 2.75); (5.19; 4.11); (56.96; 73.76)] respectively. The paper test revealed that the health of the udder is influenced by any variation in cleanliness and the ITH whose correlation coefficient is equal to 0.72 leading to the appearance of subclinical mastitis during the cold season. While during the hot season the bad milking procedure is incriminated in the appearance of hyperkeratosis lesion at a mean value equal to 1 (smooth ring stage) inducing the appearance of clinical mastitis with p less than 0.05, moreover the cows in first lactation are the most influenced by these elicited factors. In conclusion, monitoring and evaluating the well-being of the udder around the parturition is a tool that allows better prevention of mastitis.

Monsoon, post monsoon rainy days analysis by using normal, binomial distribution and discrete probability for south Gujarat

The analysis will be conducted for standard weekly (SW) 22 to 47 of monsoon and post monsoon season at south Gujarat. The standard weekly rainy days analysis of binomial distribution for monsoon season of Navsari on chi-square test on binomial distribution was found in standard week (SW) 22 to 31, 33 and standard week (SW) 35 to 39 and post monsoon in standard week (SW) 41 to 44 shows significant. The result also reveals that the monsoon season SW 32 and 34 and post monsoon season SW 40, 45, 46 and 47 revealed non-significant result. Analysis reveals the rainfall is not equally distributed during SW 32, 34, 40, 45, 16 and 47, so that the test of binomial distribution is a good fit. Monsoon season rainfall data of Navsari, Bharuch and Valsad reveals that the normal distribution at 10, 20 and 30% probability levels for the month of June, July, August and September shows the possibility of increasing rainy days occurrence. The Navsari and Bharuch districts during post monsoon season rainfall of months of October and November reveals decreasing tendency except Valsad district. The binomial distribution fit only those standard weeks in which rainfall is not equally distributed. The standard weekly rainy days analysis of binomial distribution on chi-square test in Bharuch was found that standard week (SW) 25 only 10% of monsoon season and in post monsoon standard week (SW) 42 and 47 shows non significant (5 and 10% level of significant) result, but SW 25 found significant at 5% level. In case of Valsad district, standard week 22 to 39 of monsoon season and in post monsoon season 41, 42, 43 and 46 standard weeks shows significant result. The result reveals that the monsoon season of Bharuch standard weeks 22 to 39 except from 25 and post monsoon 40, 41, 43, 44, 45 and 46 shows significant result. Further, in Valsad district standard weeks 40, 44, 45 and 47 shows significant result. The trend analysis of rainy days shows that increasing trend in monsoon season and decreasing trend in post monsoon season of Navsari, Bharuch and Valsad districts. From above results observed that the rainfall distribution is not equally distributed so test of binomial distribution at above given standard week is a good fit. The data also shows that, decreasing tendency in rainfall was observed except Valsad district.

The Scientific Profiles of Documented Collections via Publication Data: Past, Present, and Future Directions in Forensic Anthropology

Human osteological documented collections (DCs), also referred to as “identified collections”, are a valuable resource in biological and forensic anthropology, as they offer the possibility for hypothesis-driven research on sex and age-at-death estimation methods, human variability, and other morphometric-based parameters of individual identification. Consequently, they feature in many publications addressing the forensic sciences. The paper aims to explore the scientific profiles of DCs via publication using bibliometric data. The Dimensions databases were used to select the DC-related keywords in the title and abstracts of the publications. The search result analysis and extraction were conducted using VOSviewer. A total of 376 articles were found, published between 1969 and 2021 (November). The number of publications has increased over the years, specifically after 2011. The results show that most of the publications are associated with countries such as the United States and Portugal (the latter highlights the University of Coimbra), that the research tends to focus on human biological profiling (e.g., age, sex assessments), and that the journals with the highest numbers of publications were related to forensic sciences. This analysis shows a positive correlation between DC publications and the growth of forensic anthropology in recent years, with a slight shift towards the leading institutions that publish DC-based research. Hence, we can anticipate a change in the institutional leading profiles in the years to come.

Risk Factor Recognition for Automatic Safety Management in Construction Sites Using Fast Deep Convolutional Neural Networks

Many industrial accidents occur at construction sites. Several countries are instating safety management measures to reduce industrial accidents at construction sites. However, there are few technical measures relevant to this task, and there are safety blind spots related to differences in human resources’ capabilities. We propose a deep convolutional neural network that automatically recognizes possible material and human risk factors in the field regardless of individual management capabilities. The most suitable learning method and model for this study’s task and environment were experimentally identified, and visualization was performed to increase the interpretability of the model’s prediction results. The fine-tuned Safety-MobileNet model showed a high performance of 99.79% (30 ms), demonstrating its high potential to be applied in actual construction sites. In addition, via visualization, the cause of the model’s confusion of classes could be found in a dataset that the model did not predict correctly, and insights for result analysis could be presented. The material and human risk factor recognition model presented in this study can contribute to solving various practical problems, such as the absence of accident prevention systems, the limitations of human resources for safety management, and the difficulties in applying safety management systems to small construction companies.

Experimental Investigation on the Pressure Distribution Law and Calculation Method of Muddy Water with High Silt Content

The pressure distribution law of muddy water with high silt content has great influence on the stress and strain calculation of the dam body. Currently, there is a few research studies referring to the calculation method of high silt content muddy water pressure, which leads to no reliable theoretical basis for muddy water pressure calculation in dam design. In this paper, muddy water with high silt content was prepared and the imitation tests and model tests were carried out to investigate the pressure distribution law. Based on the test result analysis, it is indicated that the muddy water with high silt content is also in a flowable and viscous state, which is consistent with the law of fluid behavior; the horizontal pressure is equal to the vertical pressure at the same position, and this relationship is generally time independent; through the test result analysis, a pressure formula for muddy water with high silt content is proposed; through comparison between the pressure formula-calculated results and monitoring data, it is indicated that the proposed pressure formula is applicable in the calculation of muddy water pressure. The formula can be a useful tool in the dam safety and design calculation.

M2UNet++

Liver segmentation is instrumental for decision making in the medical realm for the diagnosis and treatment planning of hepatic diseases. However, the manual segmentation of the hundreds of CT images is tedious for medical experts. Thus, it hampers the segmentation accuracy and is reliant on opinion of the operator. This chapter presents the deep learning-based modified multi-scale UNet++ (M2UNet++) approach for automatic liver segmentation. The multi-scale features were modified channel-wise using adaptive feature recalibration to improve the representation of the high-level semantic information of the skip pathways and improved the segmentation performance with fewer computational overheads. The experimental results proved the model's efficacy on the publicly available 3DIRCADb dataset, which offers significant complexity and variations. The model's dice coefficient value is 97.28% that is 7.64%, and 2.24% improved from the UNet and UNet++ model. The quantitative result analysis shows that the M2UNet++ model outperforms the state-of-the-art methods proposed for liver segmentation.

An Improved Text Extraction Approach with Auto Encoder for Creating Your Own Audiobook

As we all know, listening makes learning easier and interesting than reading. An audiobook is a software that converts text to speech. Though this sounds good, the audiobooks available in the market are not free and feasible for everyone. Added to this, we find that these audiobooks are only meant for fictional stories, novels or comics. A comprehensive review of the available literature shows that very little intensive work was done for image to speech conversion. In this paper, we employ various strategies for the entire process. As an initial step, deep learning techniques are constructed to denoise the images that are fed to the system. This is followed by text extraction with the help of OCR engines. Additional improvements are made to improve the quality of text extraction and post processing spell check mechanism are incorporated for this purpose. Our result analysis demonstrates that with denoising and spell checking, our model has achieved an accuracy of 98.11% when compared to 84.02% without any denoising or spell check mechanism.

The application of modified thermodynamic system correction method to secondary reheat steam turbine

In order to calculation the enthalpy of wet steam in the secondary reheat turbine thermal system the thermodynamic system of the secondary reheat steam turbine based on the isentropic ideal expansion process line was corrected, This method simplifies the correction calculation step and increases the accuracy of the correction result. Analysis of the rationality of the improved method shows that: Compared with the existing secondary reheat steam turbine thermal system correction method, the maximum error of the improved thermal system correction method is 0.14%. Therefore, this method can better meet the test accuracy requirements.

Demotivation Factors in Using English as Daily Communication in EFL School: Case Study of EFL Learners

This study aimed to describe the causes of students' demotivation in using English for daily communication and find its solutions. The present researcher used the descriptive qualitative method. It was conducted on EFL Learners. There were 15 students to be participants in this study. The data were collected by observing, interviewing, and giving questionnaires to participants about English usage in their Islamic boarding schools. The participants' answers and the video of their daily communication were analyzed by interpreting the handy camera and checking the result of interpretation to the result of questioner and interview. Second, the present researcher compared the result of the handy camera, questioner, and interview to the existing theory to determine the causes of students' demotivation in using English as daily communication and its solution. The result analysis showed that the cause of students' demotivation is their lack of ability to use English, especially in mastering vocabulary and its pronunciation. Other factors were learning contents and materials, teachers, and failure experience. In addition, they prefer to use Arabic because Arabic has been rooted as daily communication in that Islamic boarding school. In comparison, the solution for that problem is that the teachers should pay considerable attention to the students' English ability, especially mastering and pronouncing vocabulary. Also, the teachers are suggested to pay more attention to teaching methods and their behavior to increase students' motivation and interest in second language learning. In addition, the teachers should explicitly make a regulation to divide a period for the student to speak English and Arabic.

Competency Development Salt Farmers Skills in Pademawu Sub-District Pamekasan Regency

Many salt-farmers in Pademawu lived in the middle to lower economic class because they still produced bad raw-salt. This study aimed to arrange a new model of developing salt-farmers skill to produce a high amount of salt in better quality. Qualitative method was used in this study. The data presented were the result of interview and observation. The researher acted as a research intrument that went directly to the fielt to obtain accurate data. The data analysis technique used was domain analysis, which sought to analyze general descriptions of research object at surface level but relatively intact about the object of research. The result analysis of this study was targetted to obtain complete description of the object without mentioned detail elements of the object research. This research only discusses the development of salt farmer skills competency. This research was expected to give valuable contribution of model of developing salt-farmers skills.