Miracle-dz/UniFAR-FTUs huggingface dataset:
Projected economic losses from milk performance detriments under heat stress in Quebec dairy herds

Abstract: The objective of this study was to estimate economic losses associated with milk performance detriments under different climate scenarios. A dataset containing milk records of Holstein and daily temperature–humidity indexes compiled over 6 yr in two contrasting climatic dairy regions of Quebec [eastern (EQ) and southwestern Quebec (SWQ)] was used to develop equations for modeling milk performance. Milk performance, including milk, fat, protein, and lactose yields of dairy herds (kg·d−1), were then projected considering six plausible climate scenarios during a climatic reference period (REF: 1971–2000) and two future periods (FUT1: 2020–2049; FUT2: 2050–2079). Economic losses were assessed by comparing future to reference milk prices based on components. Results indicated that fat and protein yields could decline in the future, thus resulting in economic losses ranging from $5.34 to $7.07 CAD·hL−1 in EQ and from $5.03 to $6.99 CAD·hL−1 in SWQ, depending on the amplitude of future temperature and humidity changes and on whether it is milk quota or cow number which is adjusted to avoid under-quota production. The projected increase in occurrence and duration of heat stress episodes under climate change could result in substantial financial harm for producers, thereby reinforcing the necessity of implementing heat-abatement strategies on dairy farms.
Symptomatische und asymptomatische Karotisstenose: leitlinienbasierte Therapie

Arteriosklerotische Veränderungen der A. (Arteria) carotis finden sich bei etwa 4% der Erwachsenen der Allgemeinbevölkerung und weisen eine steigende Prävalenz ab dem 65. Lebensjahr auf (6–15%). Bezogen auf Deutschland bedeutet dies, dass dort etwa 1 Million Menschen mit einer mindestens 50%igen Karotisstenose lebt. Insgesamt werden ca. 15% aller ischämischen Schlaganfälle durch Stenosen oder Verschlüsse der extrakraniellen A. carotis interna verursacht. Die Mehrheit der zerebralen Ischämien kann auf kardioembolische und mikroangiopathische Prozesse zurückgeführt werden. Eine hämodynamisch bedingte zerebrale Minderversorgung liegt bei lediglich 10% der betroffenen Personen mit Karotisstenosen vor. Immerhin bei 15% der Betroffenen bleibt die Schlaganfallursache unerkannt (okkulte Ischämie). Bei einer Gesamtzahl von jährlich mehr als 200 000 ischämischen Schlaganfällen würde dies für Deutschland eine Inzidenz von bis zu 30 000 karotisassoziierten Schlaganfällen pro Jahr bedeuten. Der Prävention karotisbedingter Schlaganfälle durch konservative, endovaskuläre und operative Therapieverfahren kommt somit eine große Bedeutung zu [1].
Enhanced thresholding-based wavelet noise filtering in optical fiber communications

Nowadays, the growing requirement of higher data transmission rates for real-time applications of communication systems. The capacity of data transmission increased with the higher carrier frequency. Optical Fiber Communication (OFC) systems gained a significant interest of researchers due to its capability of enhancing the data-carrying capacity. The optical waves in OFC systems operate in the range of THz those results in the increased capacity of data-carrying. The OFC systems achieved a high data rate, however, suffered from the challenges of various noises. The presence of noises in OFC may degrade the transmitting signal quality & increases the error rates. The OFC systems design by considering the noise in optical communication links recently received great interest from researchers. In this paper, we first presented the OFC design with noises such as white Gaussian noise, shot noise, & thermal noise. Secondly, the impact of noises in OFC analyzed through simulation results by performing optical communications with & without noises. Third, to suppress the noise effects on optical communications, we propose the enhanced thresholding-based wavelet Denoising approach called Wavelet Denoising using Enhanced Thresholding (WDET). The aim of WDET for optical communications is to improve the signal quality & minimize the signal errors effectively in the presence of various noises. The design of WDET is based on the properties of hard & soft thresholding of wavelet Denoising. The simulation results show that the proposed Denoising approach improves the signal quality factor with reduced Bit Error Rate (BER) & Mean Square Error (MSE) compared to existing filtering methods.
Effect of Competence, Independence, Time Pressure and Professionalism on Audit Quality (Inspeção Geral Do Estado in Timor Leste)

This study aims to analyze and explain: (1) competence has a positive effect on audit quality at the Inspecao Geral do Estado in Timor Leste; (2) independence has a positive effect on audit quality at the Inspecao Geral do Estado in Timor Leste; (3) time pressure negatively affects audit quality at the Inspecao Geral do Estado in Timor Leste; (4) professionalism has a positive effect on audit quality at the Inspecao Geral do Estado in Timor Leste. The population in this study was 30 internal auditors at the Inspecao Geral do Estado in Timor Leste, so the whole sample was taken. Thus the use of the entire population without having to draw the research sample as a unit of observation is called a census technique. The findings of this study are that competence has a positive effect on audit quality, indicating that the better the competence of the auditor, the higher the quality of the audit in an institution, or the lower the competence of auditors, the lower the probability of auditor quality in that institution, the independence has a positive effect on audit quality. The high independence of the auditor, such as a mental attitude that is free from influence, not controlled by other parties, it will improve audit quality in government agencies, time pressure has no significant negative effect on audit quality, indicating that the less time given to the auditor, the lower the audit quality, professionalism has no effect on audit quality, indicating that the better professionalism the auditor has, the lower the resulting audit quality.
Dielectric spectroscopy of PVA-Ni0.5Zn0.5Fe2O4 polymer nanocomposite films

ABSTRACT This paper seeks to address the AC electrical properties of polyvinyl alcohol (PVA)-Ni0.5Zn0. 5Fe2O4 nanocomposites with different weight ratios (PVA/Ni0.5Zn0.5Fe2O4 = 100/0, 95/5, 85/15, and 50/50) in the temperature ranging from 323 to 403 K at the frequencies from 0.01 Hz to 20 MHz. The real part of the complex permittivity (ԑʹ) was enhanced with both the temperature and concentration of Ni0.5Zn0. 5Fe2O4 nanocrystals, which originates from nano-capacitor structures experiencing interfacial polarization. These nanocomposites were shown to enhance the imaginary part (ԑ″) with the temperature, which was attributed to mobile charge carriers along conductive fillers. The static (ԑs) and infinity (ԑ∞) permittivity were obtained from Cole–Cole plots and showed an increase with temperature. The relaxation time (τo) and molecular relaxation time (τm) showed temperature dependence and decrease with increasing the temperature. The Gibbs free energy (G), enthalpy (ΔH), and the entropy (ΔS) of the activation are estimated. The ac conductivity showed frequency and temperature dependence and the charge carrier transport follow correlated barrier hopping model (CBH). The Austin-Mott model was applied to the nanocomposites and showed that the density of states at the Fermi level increased with increasing the temperature.
Conformational Changes of α-Crystallin Proteins Induced by Heat Stress

α-crystallin is a major structural protein in the eye lenses of vertebrates that is composed of two relative subunits, αA and αB crystallin, which function in maintaining lens transparency. As a member of the small heat-shock protein family (sHsp), α-crystallin exhibits chaperone-like activity to prevent the misfolding or aggregation of critical proteins in the lens, which is associated with cataract disease. In this study, high-purity αA and αB crystallin proteins were expressed from E. coli and purified by affinity and size-exclusion chromatography. The size-exclusion chromatography experiment showed that both αA and αB crystallins exhibited oligomeric complexes in solution. Here, we present the structural characteristics of α-crystallin proteins from low to high temperature by combining circular dichroism (CD) and small-angle X-ray scattering (SAXS). Not only the CD data, but also SAXS data show that α-crystallin proteins exhibit transition behavior on conformation with temperature increasing. Although their protein sequences are highly conserved, the analysis of their thermal stability showed different properties in αA and αB crystallin. In this study, taken together, the data discussed were provided to demonstrate more insights into the chaperone-like activity of α-crystallin proteins.
Meat characteristics of red jungle fowl (Gallus gallus Spadiceus), Malaysian domestic chickens (Gallus gallus Domesticus) and commercial broiler

The meat characteristics of Red jungle fowl (Gallus gallus Spadiceus) and Malaysian Domestic chicken (Gallus gallus Domesticus), which are known as slow growing birds, were studied. Results were compared with those of the commercial broilers (ROSS) which are fast growing birds. The objective of the study is to determine the meat characteristics (pH, muscle fibre diameter and collagen content) of the breeds and the correlation to their meat quality. For this purpose, a total of 90 chickens (30 chickens for each breed) were used in this study. The chickens in each group were sacrificed at 20, 56 and 120 days posthatching. Findings indicated that collagen content, pH, cooking loss and shear force values in Red jungle fowl and Malaysian Domestic chicken were significantly higher P<0.05) than the commercial broilers. The smaller muscle fibre diameters and lower glycogen reserved contributed to higher pH. Meanwhile, the collagen content showed significantly (P<0.05) positive correlation to shear force and more prominent factors than the size of muscle fibre that determines tenderness of the meat. The commercial broilers’ meat is much tender than that of the Malaysia Domestic chicken and Red jungle fowl.
Supplementation of two sources and three levels of iodine in the diet of laying hens: effects on performance, egg quality, serum and egg yolk lipids, antioxidant status, and iodine accumulation in eggs

Abstract In total, 378 Shaver White layers were allocated into 7 treatments with 6 replicates, from 30 to 42 wk of age, to assess the effects dietary organic (ethylenediamine dihydroiodide [EDDI]) versus inorganic (calcium iodate [CIOD]) iodine in laying hens. A basal diet served as control while the remaining six diets were supplemented with either CIOD (CIOD2, CIOD4, and CIOD8) or EDDI (EDDI2, EDDI4, and EDDI8) to provide 2.0, 4.0, and 8.0 mg of added iodine/kg of diet, respectively. Performance and egg quality were not affected by adding 2.0 or 4.0 mg/kg of iodine to the diets. However, a progressive decline in egg performance and feed intake occurred with EDDI8 and CIOD8 diets. The EDDI8 diet also increased abnormal eggs in parallel with decreasing the eggshell strength and Haugh unit and disturbing the serum and egg yolk lipids. This trend was connected with increase in triiodothyronine (T3) and thyroxine (T4), which led to oxidative stress in serum and egg contents. The iodine levels of eggshell and egg contents were increased by dietary iodine in a dose and time-dependent manner, while the effect of EDDI was higher than CIOD at all levels. To summary, supplementation of diets with 2 or 4 mg/kg of iodine as CIOD and specifically EDDI increased the iodine content of eggs without adverse effect on hen performance and egg quality traits. However, considering the time-dependent nature of this increase, a 12-wk period of supplementation might be not sufficient to achieve a specified level of iodine in the eggs. Highlights Diet supplementation with 2, 4, and 8 mg/kg of iodine as CIOD and EDDI increased iodine content of eggs. The highest level of iodine, especially as EDDI, diminished egg performance and egg quality connected with an increase in serum T3 and T4, which led to oxidative stress. A 12-wk period of supplementation appears to be not sufficient to achieve a specified level of iodine in the egg.
Viability of using Convolutional Neural Networks for Real-Time Fescue and Sheep Sorrel Detection in Wild Blueberry Fields

—Wild blueberry (Vaccinium angustifolium Ait.) production is hindered by weeds such as fescue (Festuca filiformis Pourr.) and sheep sorrel (Rumex acetosella L.). Commercial sprayers provide a uniform application of herbicide regardless of the incidence of weed coverage. Traditional methods of spot-applying herbicide to target weed locations relied on colour co-occurrence matrices that were limited by long processing times in addition to green colour segmentation lacking the ability to discriminate between weeds and crop canopy of similar colour. Deep learning convolutional neural networks (CNNs) are a modern processing technique which often uses powerful graphics processing units (GPUs) to classify images or detect objects within images. This novel research study featured two object-detection CNNs, YOLOv3 and YOLOv3-Tiny, trained to detect fescue using images of wild blueberry fields captured during application timing intervals in the 2019 growing season. A custom-built desktop computer using the Ubuntu 16.04 operating system and an NVIDIA GeForce RTX 2080 Ti GPU was used to test the CNNs using 1280x720 resolution images. YOLOv3 classified fescue images with an F1-score of 0.95 and YOLOv3-Tiny classified fescue images with an F1-score of 0.97. YOLOv3 and YOLOv3-Tiny classified sheep sorrel images with F1-scores of 0.93 and 0.89 respectively. A laptop running Windows 10 Pro with an NVIDIA Quadro RTX 5000 GPU was used to process video streams from four USB cameras simultaneously. YOLOv3 processed each video stream at an average framerate of 4.7 FPS using 9.2 GB of vRAM, while YOLOv3-Tiny processed each video stream at an average framerate of 20.5 FPS using 3.2 GB of vRAM. Initial results suggest that YOLOv3-Tiny can be deployed for use with a machine vision system to detect fescue and sheep sorrel in real-time for spot application of herbicide in wild blueberry fields. Using CNNs to selectively spray herbicide will appreciably reduce the volume of herbicides needed to manage wild blueberry fields, resulting in cost-savings for producers.
The role of leadership in improving the productivity of the organization through employees’ performance: A case study of the oil and gas sectors

Leadership is an integral part of the organization with a direct impact on organizational productivity and profit. The desirous leader is considered the one who can get the best from their employees to achieve the organizational goals. Thus, the appropriate leadership style, according to the needs of the organization, has a positive impact on organizational performance. This study was conducted with the aim of investigating the effects of transformational leadership on staff productivity. In this regard, data is collected from 638 participants using different means. The key parameters which are considered in this research are 360-degree scores, attendance, quality of work, and promoted score. The results revealed that in the oil and gas sector, the employees are quite optimistic about the leadership, and they believe that their immediate team leaders have a significant role in improving their performance.
Customer Satisfaction Assessment of E-Supply Chain Quality in Online Shopping: A Case Study

Purpose The purpose of this study, by introducing the concept of service quality (SQ) in E-supply chain management(E-SCM) and its impact on increasing Customer Satisfaction (CS), is to examine the influence of Quality E-Supply Chain Management Services in CS in online shopping. Design/methodology/approach After a comprehensive review of the literature, four key factors for measuring the E-supply chain, four key factors for measuring CS, and four factors for measuring the quality of identification services were selected. Then, the proposed conceptual model was presented. To validate this model, the data were collected through a survey of 150 respondents to diagnose customers’ satisfaction including online customers of online websites in Iran. The model and their interrelationships were examined based on the partial least square-structural (PLS), and model fit indices were calculated. Sample data was analyzed using SPSS21 and PLS, and model fit indices were calculated. The proposed model was validated using factor analysis and structural equation modeling techniques. Findings The results indicated that E-SCM has a direct impact on CS. The effect of SQ is also confirmed. There is a positive and significant relationship between E-SCM and CS, E-SCM and SQ, and also, SQ and CS (P> 0.05). Research limitations/implications The first limitation was convincing respondents to cooperate with the researcher. The second one, there is a lack of research-related background due to its new subject matter.
Animatronic robot with Telepresence vision

- We have been using tele operated robots in various industrial and military applications to reduce human efforts and avoiding endangering human life. Nearly all operating robots are controlled using a pc, keyboard or joystick and image or video captured with camera is seen on a monitor. Due to this tradition approach there is a gap between human operator wants to do and what robots do in actual. Robot can’t perform exact action human want them to perform due to less interactive input system. Which reduce accuracy of the system and hence reducing the capabilities of the robot. Our project is to work on a new approach with hardware and software system which will bridge this gap.
A comprehensive review of the healthy worker effect in occupational epidemiological studies

The reduction of mortality and morbidity rates among occupational cohort studies may be attributed to the presence of the healthy worker effect (HWE). Occupational epidemiologic studies investigating worker’s health are prone to the risk of having the HWE phenomenon and this special form of bias has been debated over the years. Hence, it’s imperative to explore in-depth the magnitude and sources of HWE, and further, elucidate the factors that may affect HWE and strategies reducing HWE. The HWE should be considered as a mixed bias between selection and confounding bias. The validity threats due to the HWE among morbidity studies are the same as the mortality studies. The consequent reduction due to the HWE in the association between the exposure and outcome may lead to underestimating some harmful exposures in the workplace or occupational settings. Healthy hire effect and healthy worker survivor effect are the main sources of HWE. Several factors can increase or decrease the probability of HWE; therefore, the investigators should consider them among future occupational epidemiological studies. Many strategies can help in reducing the impact of HWE, but each strategy has its weaknesses and strengths. Not all strategies can be applied among all occupational epidemiological studies. Mathematical procedures still need further investigations to be validated. HWE is a consequence of inappropriate comparison groups in nature. The usage of the general population as a reference group is not an appropriate choice. By considering the HWE sources and factors and using appropriate strategies, the impact of HWE may be reduced.
Two rare shield depictions from the Burrungkuy rock art region of Western Arnhem Land, Australia

Abstract Shields were not known to have been made or used in western Arnhem Land, northern Australia, since European contact and possibly as a consequence are rarely found in the rock art of the region. However, during a recent survey of rock art sites in the Burrungkuy region of Kakadu two shields, or shield-like implements, were recorded in one shelter. This paper documents these motifs and discusses the cultural significance of shields in other parts of Australia, including as traded items, and offers suggestions as to how such depictions of these ‘exotic’ implements might have come to be in Arnhem Land. The paper concludes that some shields may have found their way into the Arnhem Land region via the extensive trade and exchange networks that connected communities across the continent for millennia and were depicted as a result of items collected by locals or observed by those involved in the trade.
Detecting plant species in the field with deep learning and drone technology

Aerial drones are providing a new source of high‐resolution imagery for mapping of plant species of interest, amongst other applications. On‐board detection algorithms could open the door to allow for applications in which drones can intelligently interact with their environment. However, the majority of plant detection studies have focused on detection in post‐flight processed orthomosaics. Greater research into developing detection algorithms robust to real‐world variations in environmental conditions is necessary, such that they are suitable for deployment in the field under variable conditions. We outline the steps necessary to develop such a system, show by example how real‐world considerations can be addressed during model training and briefly illustrate the performance of our best performing model in the field when integrated with an aerial drone. Our results show that introducing variations in brightness as an additional augmentation strategy during training is beneficial when dealing with real‐life data. We achieved a 27% improvement in the F1‐score obtained on the unseen test set when using this approach. Further improvements to the model performance were obtained through the use of weight map‐based loss, accounting for uncertainty in the annotation masks due to the indistinct nature of the edges of the target plants using weighting. This resulted in a 15% improvement in precision for the best configuration of hyper‐parameters, yielding a final model with an F1‐score of 83% and accuracy of 96%. Finally, results computed on the fly show that such a system is deployable in the field. This study shows that it is possible for a commercially available drone, integrated with a deep learning model, to detect invasive plants in the field and demonstrates methodology which could be applied to developing similar systems for other plant species of interest. The ability to perform detection on the fly is necessary for future applications in which intelligent interaction between a drone and its environment is required.