Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Heat Stress on Follicular Physiology in Dairy Cows

Simple Summary Environmentally induced hyperthermia, also called heat stress (HS), compromises reproductive physiology in mammals. The number of oocytes is fixed after birth and they are stored in the ovary in a quiescent state (at the stage of the first meiotic prophase) in primordial follicles. There is evidence that HS alters the oocyte quality, the dynamics of follicular growth and ovulation. The dairy cow, submitted to the metabolic stress of high milk production, is a good model for studying the effects of HS on ovarian function. The aim of this review is to describe the influence of HS during the stages of follicular development in dairy cattle, from the activation of primordial follicles to ovulation. Some clinical aspects are also considered. Abstract Follicular organization starts during mid-to-late fetal life with the formation of primordial follicles. The bilateral interplay between the oocyte and adjoining somatic cells during follicular growth and ovulation may be sensitive to heat stress (HS). Mechanisms giving rise to pre-ovulatory temperature gradients across reproductive tissues are mostly regulated by the pre-ovulatory follicle, and because the cooling of the gonads and genital tract depends on a counter-current transfer system of heat, HS may be considered a major factor impairing ovulation, fertilization and early embryo development. There is evidence of a long-lasting influence of HS on oogenesis and final follicular maturation. Follicular stages that are susceptible to HS have not been precisely determined. Therefore, the aim of this review was to describe the influence of HS during the staged follicular development in dairy cattle, from the activation of primordial follicles to ovulation. Some clinical prospects are also considered.
Sustainability of Transportation Structures Using Composite Materials to Support Trade and Growth

Corrosion-induced deterioration of steel rebar is one of the main reasons for repair and rehabilitation programs for conventional steel-reinforced concrete bridge decks. According to the National Association of Corrosion Engineers (NACE), of all bridges in the United States, over 50 percent are constructed of conventional steel-reinforced or prestressed concrete, and one in three bridges is considered structurally deficient or functionally obsolete due to corrosion of steel reinforcement. NACE has estimated the annual cost of corrosion-related maintenance of highway bridges in the United States at $8.3 billion. To overcome corrosion-induced structural issues, researchers have introduced and applied fiber-reinforced polymer (FRP) bars, over the past couple of decades, as a corrosion-resistant candidate for either conventional reinforcing steel or prestressing strands. High strength-to-weight ratio, corrosion resistance, and accelerated construction due to ease of placement of the bars and implementation are the special characteristics that make these bars an appealing alternative for either steel-reinforcing bars or prestressing strands. This report presents the experimental and analytical investigations of structural performance of a full-scale American Association of State Highway and Transportation Officials (AASHTO) I-girder Type I, reinforced and prestressed with aramid-fiber-reinforced polymer (AFRP) bars, where the bridge girder is composite with a topping deck. The major objectives of this research included evaluating (1) the constructability, (2) the load and deformation capacities under either flexure or shear tests, and (3) the structural performance per AASHTO load and resistance factor design (LRFD) criteria. The results of this research confirm the adequate strength and deformation capacities of the composite girder, satisfying the AASHTO LRFD criteria. The flexural capacity of the composite girder was about 1582 kNm (1167 kft.), which is 20 percent greater than the maximum factored load, 1326 kNm (978 kft.), per AASHTO LRFD. Under the flexure test, the failure mode of the girder was recognized as the tendon rupture in the bottom flange, where the maximum compressive strain in the topping deck did not reach a failure value equal to −0.003. Such a failure mode was expected because it is not practical to fit too many FRP bars within the bottom flange of the girder to over-reinforce the section and change the failure mode from tendon rupture to concrete crushing in the top fiber of the section.
Development of Nonlaboratory-Based Risk Prediction Models for Cardiovascular Diseases Using Conventional and Machine Learning Approaches

Criticism of the implementation of existing risk prediction models (RPMs) for cardiovascular diseases (CVDs) in new populations motivates researchers to develop regional models. The predominant usage of laboratory features in these RPMs is also causing reproducibility issues in low–middle-income countries (LMICs). Further, conventional logistic regression analysis (LRA) does not consider non-linear associations and interaction terms in developing these RPMs, which might oversimplify the phenomenon. This study aims to develop alternative machine learning (ML)-based RPMs that may perform better at predicting CVD status using nonlaboratory features in comparison to conventional RPMs. The data was based on a case–control study conducted at the Punjab Institute of Cardiology, Pakistan. Data from 460 subjects, aged between 30 and 76 years, with (1:1) gender-based matching, was collected. We tested various ML models to identify the best model/models considering LRA as a baseline RPM. An artificial neural network and a linear support vector machine outperformed the conventional RPM in the majority of performance matrices. The predictive accuracies of the best performed ML-based RPMs were between 80.86 and 81.09% and were found to be higher than 79.56% for the baseline RPM. The discriminating capabilities of the ML-based RPMs were also comparable to baseline RPMs. Further, ML-based RPMs identified substantially different orders of features as compared to baseline RPM. This study concludes that nonlaboratory feature-based RPMs can be a good choice for early risk assessment of CVDs in LMICs. ML-based RPMs can identify better order of features as compared to the conventional approach, which subsequently provided models with improved prognostic capabilities.
DESIGN OF A SIMPLE LOW-COST QUARTZ CRYSTAL MICROBALANCE SYSTEM

This article describes a simple design of a low-cost, real-time, and computerized quartz crystal microbalance system. The system measures resonance frequencies up to 6 MHz with a resolution of 1 Hz, i.e., it can monitor mass change in the range of nano-gram and thickness change in the range of micrometer. The designed system consists of three main parts: input circuitry, control, and counting parts. In the input circuitry, three separated input signals types are allowable: the first is direct TTL compatible, the second is analog signal, while the third is the signal that may come from the quartz crystal microbalance. The last two signals are converted to TTL signals using wave-shaping circuitry. The control part is interfaced with the status and control ports of the computer LPT1 parallel port. It consists of time base circuitry and different multiplexers to control data sending to computer according to the input signal under investigation. The counter consists of six binary counters in cascade and directly interfaced to the computer through the LPT1 data port; the transfer process was carried out by two different ways according to the measuring mode of the system. All parts were controlled by specially designed software. Finally, the frequency readings of the quartz crystal microbalance were found to be in good agreement with those of a frequency counter model GFC-8055G connected in parallel during an experiment performed to test the system.
Automatic current shaper with fast output regulation and soft-switching

A new utility-to-DC, harmonic-free interface combines the functions of automatic input current shaping, fast output voltage regulation, and lossless, soft switching in a single power converter. This was made possible through internal energy storage and the discovery of new modes of operation, which together, effectively decoupled the input boost-like part of the Cuk converter from its buck-like output. Experimental results obtained on a 50 W-12 V prototype confirm the fast output regulation (30 kHz bandwidth for 100 kHz switching frequency) simultaneously with low-harmonic line current waveforms. <<ETX>>
MiRNA-Nanofiber, the Next Generation of Bioactive Scaffolds for Bone Regeneration: A Review

Scaffold-based bone tissue engineering has been introduced as an alternative treatment option for bone grafting due to limitations in the allograft. Not only physical conditions but also biological conditions such as gene expression significantly impact bone regeneration. Scaffolds in composition with bioactive molecules such as miRNA mimics provide a platform to enhance migration, proliferation, and differentiation of osteoprogenitor cells for bone regeneration. Among scaffolds, fibrous structures showed significant advantages in promoting osteogenic differentiation and bone regeneration via delivering bioactive molecules over the past decade. Here, we reviewed the bone and bone fracture healing considerations for the impact of miRNAs on bone regeneration. We also examined the methods used to improve miRNA mimics uptake by cells, the fabrication of fibrous scaffolds, and the effective delivery of miRNA mimics using fibrous scaffold and their processes for bone development. Finally, we offer our view on the principal challenges of miRNA mimics delivery by nanofibers for bone tissue engineering.
Editorial Statement: The Globalization of Psychology, the Psychology of Globalization

We are pleased to present the thirty fourth volume of the Bethlehem University Journal as a special issue on psychological research in Palestine and the world. This special issue draws from original papers and other related scholarship presented at the First Annual International Psychology Conference entitled, “Psychological Research in Palestine between Theory and Practice,” which was held at Bethlehem University, Bethlehem, Palestine, from April 22-23, 2016.
Temporal fluctuation of patchy stomatal closure in leaves of Dipterocarpus sublamellatus at upper canopy in Peninsular Malaysia over the last decade

In the southeast Asian lowland dipterocarp forest of Peninsular Malaysia (Pasoh Forest Reserve), upper canopy tree species with heterobaric leaves show severe midday depression of net assimilation rate ( A ) accelerated by patchy stomatal closure, although it is still unclear whether it always happens or not. We added the in situ observations at various meteorological conditions over the last decade to evaluate the frequency and environmental conditions of patchy stomatal closure in Dipterocarpus sublamellatus Foxw. , an emergent tree with heterobaric leaves through leaf–gas exchange measurements combined with numerical simulations and chlorophyll ﬂuorescence imaging. Our observation revealed that on days with moderate leaf temperature ( ＜ 35 ℃ ) and vapor pressure deﬁcit (VPD), which consist four of nine measurement days during 2003 (cid:514) 2015, uniform stomatal behavior could explain observed A during the day. The patterns of stomatal behavior shifted from ‘ uniform ’ to ‘ patchy ’ even within a day depending on increases in leaf temperature and VPD according to irradiation of sunlight. However, it did not return from ‘ patchy ’ to ‘ uniform ’ once patchy stomatal closure happened in a day.
Continuous‐time receding‐horizon reinforcement learning and its application to path‐tracking control of autonomous ground vehicles

Reinforcement learning (RL) and approximate dynamic programming (ADP) have been recently studied to solve nonlinear optimal control problems (OCPs) of continuous‐time (CT) systems. However, online learning efficiency and reliability are two major concerns to be further improved. Motivated by the above issues, in this paper we propose a receding‐horizon reinforcement learning (RHRL) algorithm for near‐optimal control of CT systems under control constraints. Different from classic RL and ADP, in the proposed approach, the infinite‐horizon OCP is decomposed as a series of finite‐horizon ones solved with an actor‐critic structure according to the receding horizon strategy, which can improve the online learning efficiency and reliability. The unknown dynamics of the system are identified offline using a sparse kernel‐based neural network structure whose weights are also updated online in the RHRL framework to improve the control performance. Moreover, the convergence of the modeling error is proven. To verify the effectiveness of our approach, we apply the RHRL algorithm to the autonomous ground vehicle for realizing near‐optimal path‐tracking control. Compared with CT model predictive control using a nominal model and other model‐free tracking controllers such as pure pursuit, heuristic dual programming, and the soft actor‐critic algorithm, RHRL performs better in terms of control performance.
Affective-Cognitive Reward Model Based on Emotional Interactions

In this paper, author presents a new computational model where both the results of emotional interactions from the intrinsic emotion and recognition and the extrinsic environmental stimulation (another agent), the two parts play an important role in everyday life. We take a kind of six basic emotion states (happiness, surprise, anger, fear, sadness, disgust), and updates its state depending on its current emotional and cognitive state and meeting with another one in random environment. At last, we also design some experiments to verify the effects of affective cognitive algorithm. Those experimental results are accordance with the emotion principle of human being.
Mobile Device Fingerprint Identification using Gyroscope Resonance

Device fingerprint is information about the target computing device for the purpose of identification. The fingerprinting algorithm that how to assimilate the target into an identifier has been well studied for more than 20 years. However, the recent obfuscation method against device fingerprinting makes collecting this information more difficult. In order to solve these problems, this paper proposes a new type of fingerprinting method that relies on the resonant frequency response of the gyroscope. Our method first generates an ultrasonic as the trigger signal and obtains the sensor’s output through the application program or the web browser as the response. After the sensor output being normalized during the data preprocessing, resonance features are extracted after frequency domain analysis. Finally, the mobile device is identified through these features matching. In the experiment, we test many types of mobile phones to demonstrate that our method is feasible while users are unaware of this process. For instance, we find that some features are stable when the posture of the mobile device or the time change. There are 10 features based on resonance frequency that can help us improve the classification accuracy to 96.5%. The comprehensive experiments demonstrate that our method can effectively distinguish different types of mobile devices. Even if it is the same model of mobile devices with the same type of gyroscopes, this method still has a good performance.
Study on the nature of stick–slip motion for high-precision table

Friction is one of the important factors resulting in the contour error of feed servo systems for high-precision computer numerical control machine tools. The beginning criterion of friction compensation is usually based on the recognition that reverse axis velocity reaches zero at quadrant boundary in circular motion. In fact, reverse velocity cannot reach zero at quadrant boundary. This article investigates the dynamics question behind stick–slip motion, based on re-understanding friction and closed-loop control. Here, the stick–slip motions were distinguished as three kinds: positive, negative and full reversals. Moreover, it is also considered that closed-loop control system must produce inhibition to inner disturbance as to friction. The conclusion that friction compensation should take place before the velocity decreases to zero is obtained. The simulation result well illustrates the theoretical analysis of the nature of stick–slip motion. Compensation experiment shows that friction compensation considering negative friction can easily further decrease friction error in high speed.
Biomining of metals: new challenges for the next 15 years

Due to the current and future scenario in which phenomena such as global warming, massive industrial waste, excessive pollution of the ecosystem, water scarcity, among other negative variables, our planet and society, faces the urgent need to advance in the generation of more sustainable and environmentally friendly mining methods. The decline in the quality of the geological resources, specifically the increase of low‐grade minerals, has created a scenario under which mining companies must make great efforts to maintain their current production levels.
Numerical simulation of inter-flat air cross-contamination under the condition of single-sided natural ventilation

The objective of this study is to investigate the mechanism of inter-flat airborne disease transmission under the condition of single-sided natural ventilation. The focus is on one of the typical designs in residential buildings with a rectangular plan layout and having a common corridor separating the two sides, each of which has a flat façade with openable windows. When the wind speed is extremely low, with doors closed and windows opened, the flats become single-sided naturally ventilated driven by buoyancy effects. The air pollutants can travel from a lower flat to a vertically adjacent upper flat through open windows, caused by indoor/outdoor temperature-difference induced buoyancy. Computational fluid dynamics is employed to explore the characteristics of this process. Based on the comparison with experimental data about the air flow distribution in and around a single-sided naturally ventilated room, the renormalization group based k−ϵ model, together with carbon dioxide used as a tracer, is chosen to reveal this air cross-contamination. The simulation results are in agreement with our prior on-site tracer-gas measurements, revealing that the windows flush with a flat façade can be a major route of the air cross-contamination in high-rise residential buildings. Finally, an assessment index is proposed to evaluate the potential infection risks associated with this inter-flat air flow occurring in high-rise residential buildings.
High-speed rail's potential for the reduction of carbon dioxide emissions from short haul aviation: a longitudinal study of modal substitution from an energy generation and renewable energy perspective

Abstract This paper quantifies and evaluates, utilising a ‘bottom-up’ approach, the effect on CO2 emissions of a modal shift from short-haul air travel to high-speed rail (HSR), based on projected passenger movements, between Sydney and Melbourne, Australia during the period 2010–2030. To date, peer-reviewed studies assessing the CO2 emissions from these competing modes of high-speed transportation have been restricted principally to a cross-sectional assessment, with a Eurocentric bias. This present comparative study seeks to address a gap in the literature by assessing, longitudinally, the CO2 emissions associated with the proposed operation of HSR against the ‘business-as-usual’ air scenario between Sydney and Melbourne. Under the assumed 50/50 modal shift, and the Australian government's current renewable electricity target, an annual reduction in CO2 emissions of approximately 14% could be achieved when compared with a ‘business-as-usual’ air scenario. This percentage reduction represents a 62 kt reduction in base year, 2010, and a 114 kt reduction in the final year, 2030. In total, the overall reduction achieved by such a modal shift, under the assumed conditions, during the period 2010–2030, equates to approximately 1.87 Mt of CO2. Importantly, if the electrical energy supply for HSR operations was further ‘decarbonised’, then it follows that a greater emission reduction would be achieved.
Application of powerful SFC to self diagnosis of manufacturing machines in the tire industry

Proposed new troubleshooting methods for programmable controllers (PCs). Through studies of field applications in the tire industry the sequential function chart (SFC) is recognized as not only a powerful substitution for ladder logic diagram but also as useful in machine trouble diagnosis. Typical enhancements of SFC as self diagnostic function are; 1) to search the conditions which cause the machine to halt, 2) to collect logging table data for the historical program paths analysis, and 3) to specify the cause of the trouble by tracing back 1) and 2). This paper discusses the self diagnostic functions by SFC and its implementation. <<ETX>>
Early Identification and Detection of Driver Drowsiness by Hybrid Machine Learning

Drunkenness or exhaustion is a leading cause of car accidents, with severe implications for road safety. More fatal accidents could be avoided if fatigued drivers were warned ahead of time. Several drowsiness detection technologies to monitor for signs of inattention while driving and notifying the driver can be adopted. Sensors in self-driving cars must detect if a driver is sleepy, angry, or experiencing extreme changes in their emotions, such as anger. These sensors must constantly monitor the driver’s facial expressions and detect facial landmarks in order to extract the driver’s state of expression presentation and determine whether they are driving safely. As soon as the system detects such changes, it takes control of the vehicle, immediately slows it down, and alerts the driver by sounding an alarm to make them aware of the situation. The proposed system will be integrated with the vehicle’s electronics, tracking the vehicle’s statistics and providing more accurate results. In this paper, we have implemented real-time image segmentation and drowsiness using machine learning methodologies. In the proposed work, an emotion detection method based on Support Vector Machines (SVM) has been implemented using facial expressions. The algorithm was tested under variable luminance conditions and outperformed current research in terms of accuracy. We have achieved 83.25 % to detect the facial expression change.
Multiwavelength highway photonic switches using wavelength-sorting elements-design

We propose multiwavelength highway photonic switch architectures for cross-connects using the wavelength routing function of the waveguide-array-grating demultiplexer. The wavelength router is used as wavelength-sorting elements. The wavelength division multiplexed (WDM) optical signals from multiple input ports are routed to group of output ports with certain combination of wavelengths. This enables multiport WDM systems to be configured using the reduced number of wavelength demultiplexing and multiplexing elements.