Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of the cryopreservation process on dog sperm integrity

Abstract Sperm cryopreservation has become an indispensable tool in reproductive biology. However, frozen/thawed semen has a short lifespan due to loss of sperm cell integrity. To better understand which sperm cell structures are compromised by the cryopreservation process and apoptosis markers, the sperm of five healthy mature dogs was analyzed in this study. Analysis was performed after collection, cooling, and thawing via computer assisted sperm analyzer (CASA) and evaluation of membrane fluidity and permeability, phosphatidylserine translocation (Annexin V), membrane integrity, mitochondrial membrane potential, membrane lipid peroxidation (LPO) and activity of the apoptotic markers caspases 3 and 7 by flow cytometry. Cryopreservation decreased total and progressive motility and the percentage of rapid sperm (P < 0.01). Damage to sperm cells was confirmed by Annexin V (P < 0.01), indicating that capacitation-like changes were induced by the cryopreservation procedures. An increase in sperm membrane fluidity was also noted in frozen/thawed samples (P < 0.01). Plasma and acrosomal cell membranes were affected (P < 0.01), with decreases in the subpopulation displaying high membrane potential (P < 0.01). Membrane LPO was increased in thawed sperm compared to cooled sperm (P < 0.05) but was not different from that in fresh sperm. No differences were observed in caspase 3 and 7 activity after cooling, freezing, or thawing. In conclusion, total and progressive motility, plasma membrane integrity and mitochondrial membrane potential suffered from the deleterious effects caused by cryopreservation, unlike the activity of caspases that remained stable during the freezing process.
On the role of local blockchain network features in cryptocurrency price formation

Cryptocurrencies and the underpinning blockchain technology have gained unprecedented public attention recently. In contrast to fiat currencies, transactions of cryptocurrencies, such as Bitcoin and Litecoin, are permanently recorded on distributed ledgers to be seen by the public. As a result, public availability of all cryptocurrency transactions allows us to create a complex network of financial interactions that can be used to study not only the blockchain graph, but also the relationship between various blockchain network features and cryptocurrency risk investment. We introduce a novel concept of chainlets, or blockchain motifs, to utilize this information. Chainlets allow us to evaluate the role of local topological structure of the blockchain on the joint Bitcoin and Litecoin price formation and dynamics. We investigate the predictive Granger causality of chainlets and identify certain types of chainlets that exhibit the highest predictive influence on cryptocurrency price and investment risk. More generally, while statistical aspects of blockchain data analytics remain virtually unexplored, the paper aims to highlight various emerging theoretical, methodological and applied research challenges of blockchain data analysis that will be of interest to the broad statistical community. The Canadian Journal of Statistics 48: 561–581; 2020 © 2020 Statistical Society of Canada
A highly efficient surface modified separator fabricated with atmospheric atomic layer deposition for high temperature lithium ion batteries

A high throughput mass production of separator is proposed using a well‐established unique in‐house process of roll‐to‐roll atmospheric atomic layer deposition. An ultra‐thin conformal layer of Al2O3 is deposited over the commercial Celgard (PE/PP/PE) using multi‐slit gas source head. Overall 10 nm increase is incurred in the thickness, while maintaining the porosity to ~48%. The entire process of fabrication was performed at very low temperature of 90°C. The high thermal stability of as‐modified separator is achieved at of 180°C. The separator was analyzed using X‐ray photoelectron spectrometer, electrochemical impedance spectra, and field emission scanning electron microscope. The as‐developed separator showed excellent wettability due to the surface medication in addition to robust flexibility, high conformity, and minimal thermal shrinkage. The Lithium cobalt oxide (LCO)/Graphite cells with atomic layer deposition (ALD) Celgard (Al2O3 deposited) separator delivered remarkable discharge capacity with 79.5% capacity retention after 100 cycles at 1 C as compared to the uncoated‐separator(Celgard separator), which yielded relatively less retention of ~70%. Moreover, the LCO/Graphite cells with the ALD‐Celgard separator delivered the discharge capacity of 140 mAh/g at elevated temperature (up to 80°C).
A Data Mining Approach to Flight Arrival Delay Prediction for American Airlines

In the present scenario of domestic flights in USA, there have been numerous instances of flight delays and cancellations. In the United States, the American Airlines, Inc. have been one of the most entrusted and the worlds largest airline in terms of number of destinations served. But when it comes to domestic flights, AA has not lived up to the expectations in terms of punctuality or on-time performance. Flight Delays also result in airline companies operating commercial flights to incur huge losses. So, they are trying their best to prevent or avoid Flight Delays and Cancellations by taking certain measures. This study aims at analyzing flight information of US domestic flights operated by American Airlines, covering top 5 busiest airports of US and predicting possible arrival delay of the flight using Data Mining and Machine Learning Approaches. The Gradient Boosting Classifier Model is deployed by training and hyper-parameter tuning it, achieving a maximum accuracy of 85.73%. Such an Intelligent System is very essential in foretelling flights on-time performance.
‘Gametes Simulator’: a multilocus genotype simulator to analyze genetic structure in outbreeding diploid species

: Bulk sampling and subsequent DNA fingerprinting are applied to obtain estimated allelic frequency data and unveil population structure for outbreeding species. We developed ‘Gametes Simulator’, a routine to simulate gametes from allelic frequencies of unlinked loci, which enables the analysis of population structure through Bayesian analysis. Based on the allelic frequen cies in the populations, the software simulates the alleles per population in the right proportions and assigns one allele per marker to each gamete following Mendel’s laws that govern gametogenesis. multiplying an allelic frequency (Af) by the number of gametes to simulate (Gs), (Af.Gs); if the decimal part of the result is equal to or higher than 0.5 alleles, the software will round the value up to the next integer number, and if it is less than 0.5, it will return the integer number without the decimal part. For example, if Af.Gs ≥ 0.5 but < 1.5, the program will simulate 1 allele, and if Af.Gs is ≥ 1.5 and < than 2.5, it will simulate 2 alleles due to the evident fact that it is not possible to simulate decimal parts of an allele or any decimal part of a gamete (and it is also impossible for this to happen in nature). To downsize the errors due to the use of a small sample size (Gs), we strongly recommend simulate a number of gametes that make possible that the lowest allelic frequency in the input matrix then will be represented at least with one allele in the simulation. To that end, the researcher should take into account that the allele with the lowest frequency in the input matrix will be represented in the population’s sample of gametes at least once only if the sample size (Gs: number of gametes to be simulated) is as large as the quotient (q) that represents the inverse of the lowest allelic frequency ( lowest Af) in the input (q = 1/ lowest Af). To avoid inaccuracies due to the sample size, a 2q number of gametes can be simulated.
A screening method for growth-dependent genes involved in the cytotoxicity of chemicals in Saccharomyces cerevisiae

When considering mechanisms of toxicity development to chemical substances, one potentially important mechanism is the selective inhibition of proteins essential for cell growth (target molecules). In this study, to detect the target molecules of chemical substances, we established a method for comprehensively screening for essential proteins that confer resistance against chemical substances via overexpression in yeast. We used budding yeast, a common eukaryotic model organism, to produce yeast strains showing overexpression of different genes encoding essential proteins. This method was used to search for overexpressed genes conferring arsenite resistance in yeast, and as a result, we successfully identified ten types of new genes correlated with arsenite resistance.
Output-Constrained Robust Sliding Mode Based Nonlinear Active Suspension Control

The nonlinear active suspension control design can be analyzed as a multiobjective control problem that caters to the enhancement in ride comfort levels while ensuring that road holding is maintained with the constrained suspension displacement movement. In this article, a robust constrained output feedback approach employing sliding mode controllers is proposed for the nonlinear active suspension system equipped with hydraulic actuators. Adhering to mechanical design limitations, the suspension displacement and the corresponding displacement rate are constrained using asymmetric barrier Lyapunov functions. Consequently, a nonlinear control law that incorporates the first-order sliding mode control is then formulated to regulate the hydraulic valve and thereby provide an active control effort. The robust control performance with high-performance improvements for ride comfort in the presence of parametric uncertainties, sensor noise, and over variable driving velocities for different road conditions is established using simulation studies.
HEADMASTER LEADERSHIP EFFECT ON TASK LOAD OF SPECIAL EDUCATION INTEGRATION PROGRAM TEACHER

Purpose of the Study: The leadership of a headmaster at the school has a major influence on school management and teacher management. These influences also impact the task load of the Special Education Integration Program (SEIP) teacher. Various studies have been conducted in Malaysia and abroad on this issue. Based on previous studies and research on existing leadership theories, five leadership factors impact the SEIP teacher's task load, namely leadership style, attitude, knowledge, experience, and qualifications. The purpose of this study is to determine whether these factors affect the task load of the SEIP teacher. Methodology: A fully quantitative method was used in this study by distributing a set of online questionnaires to SEIP teachers across Malaysia using the Google for platform. Confirmatory Factor Analysis (CFA) through AMOS software is used for data analysis purposes. Main Findings: The findings show that all the factors mentioned in the leadership style, attitude, knowledge, experience, and competency of achievement are validated as influences on the SEIP teacher's task load. There have been several studies examining the leadership factor affecting the task load of the SEIP teacher, but the application of the CFA approach using AMOS is still underdeveloped. Therefore, the findings of this study can further confirm previous findings on this issue. Application: This research can be useful for the headmaster and the SEIP teachers to give their best in school management. Novelty: It is common to read about the issue for this research is the premier school, but this research was based on the special education field.
Evaluation of biomarkers: Galactomannan and 1,3-beta-D-glucan assay for the diagnosis of invasive fungal infections in immunocompromised patients from a tertiary care centre

Purpose: Due to limitations of traditional microbiological techniques, standardised fungal biomarker tests such as Galactomannan Index (GMI) and 1,3-beta-D-glucan (BDG) are being preferred for diagnosis of invasive fungal infections (IFIs). These tests have been extensively used in developed countries but seldom in developing countries. The present study was performed to evaluate these tests for the diagnosis of IFIs in immunocompromised patients at an Indian tertiary care centre. Materials and Methods: A retrospective hospital-based study was done in immunocompromised patients with clinical suspicion of IFI. The demographic, clinical, radiological and mycological details of the patients were recorded. The patients were categorised into proven, probable and no IFI (as per European Organization for Research and Treatment of Cancer/Mycoses Study Group criteria). The sensitivity and specificity of BDG Fungitell and Platelia Aspergillus antigen assays was estimated. Results: A total of 70 consecutive patients were included, of which 41 had IFI (10 proven and 31 probable) while 29 had no IFI. A significant association was found between IFI and the presence of a central venous line (P = 0.035) and history of intake of T-cell immunosuppressants (P = 0.001). Median BDG values (pg/ml) in patients with proven IFI, probable IFI and no IFI were 300 (range: 70–500), 165 (range: 53–500) and 45 (range: 31–500), respectively. The receiver operating characteristic (ROC) curve analysis for BDG revealed an area under the curve of 0.995, sensitivity: 97.4% and specificity: 96.6% for IFI diagnosis. The ROC curve analysis of GMI revealed an AUC of 0.75 and 90% patients with invasive aspergillosis (IA) had positive GMI. Conclusion: BDG has good sensitivity and specificity for distinguishing IFI from no IFIs and GMI may be used for diagnosing IA.
BionicDB: Fast and Power-Efficient OLTP on FPGA

Hardware specialization has been considered as a promising way to overcome the power wall, ushering in heterogeneous computing paradigm. Meanwhile, several trends, such as cloud computing and advanced FPGA technology, are converging to eliminate the barriers to custom hardware deployment, allowing it to be both technologically and economically feasible. In this paper, we conduct a pioneering study of hardware specialization for OLTP databases and present a fast and power-efficient transaction processing system built on FPGA, called BionicDB. With an order of magnitude higher power-efficiency inherently offered by FPGA, BionicDB performs faster or comparable to state-of-the-art software OLTP system by accelerating indexing and inter-worker communication.
Characterization and regulation of voltage-operated Ca2+ channels in neuroendocrine melanotrope cells of Xenopus laevis

To investigate the way by which multiple incoming neurochemical messengers control second messenger systems to evoke an unambiguous neuronal output, melanotrope neuroendocrine cells in the pars intermedia of the pituitary gland of the South African clawed toad Xenopus laevis were studied. Researches in this thesis reveal: 1) Black-adapted melanotropes express all classes of high-voltage activated (HVA) Ca2+ channels, namely the L, N, P/Q and R types, but no low-voltage-activated (LVA) Ca2+ channels. 2) The N-type and R-type channels are involved in the generation of spontaneous intracellular Ca2+ oscillations. 3) The three GiPCRs inhibit the R-type Ca2+ currents through G / subunits. 4) Activation of the DA-D2 and the NPY-Y1 receptor inhibit the N-type Ca2+ current through another, as yet unidentified mechanism. These receptors inhibit this calcium current with similar strength as they inhibit MSH secretion. 5) Synergy between the two stimulatory neuropeptides TRH and sauvagine reverses D2-receptor-induced inhibition of spontaneous Ca2+ oscillations and action current firing, whereas the individual stimulatory peptides are ineffective. The combination of TRH and sauvagine cannot reverse the D2-receptor-induced inhibition of the R- and N-type Ca2+ currents, and as a result also do not reverse the inhibition of hormone secretion. The results also indicate that the Xenopus melanotrope can generate Ca2+ oscillations that are independent of Ca2+ influx through R- and N-type Ca2+ channels. 6) Ca2+-dependent regulation of Ca2+ currents is correlated with adaptation to background light intensity: in melanotropes from white-adapted toads, Ca2+-dependent regulation of L-type Ca2+ channels is more dominant than in black-adapted melanotropes. 7) In contrast to black-adapted melanotropes, white-adapted melanotropes express LVA Ca2+ channels. In conclusion, the experiments described in this thesis have revealed some important features of the melanotrope cell and have provided new knowledge and better understanding of the mechanisms underlying integration of complex external information by neuroendocrine cells.
Tissue-mimicking phantoms for biomedical applications

Emerging biomedical instrumentation for imaging and diagnostics requires tissue-mimicking phantoms with optical properties close to those of real biological tissues. Many such tissues and organs consist of several layers with different physical properties, e.g. the head includes the brain, skull, and skin, which in turn also comprise several layers. Structure, optical and mechanical properties depend on the purpose of phantoms and studied materials and technologies. In this paper, we present both plain single-, multi-layered phantoms, and complex opto-mechanical phantoms that imitate parts of the body, in particular, the head. We describe the procedure, materials, internal structure, and tuning of the optical properties of two different phantom manufacturing methods as well as show examples of tissue-mimicking phantoms for different biomedical applications.
Log-cumulants of the finite mixture model and their application to statistical analysis of fully polarimetric UAVSAR data

Since its first flight in 2007, the UAVSAR instrument of NASA has acquired a large number of fully Polarimetric SAR (PolSAR) data in very high spatial resolution. It is possible to observe small spatial features in this type of data, offering the opportunity to explore structures in the images. In general, the structured scenes would present multimodal or spiky histograms. The finite mixture model has great advantages in modeling data with irregular histograms. In this paper, a type of important statistics called log-cumulants, which could be used to design parameter estimator or goodness-of-fit tests, are derived for the finite mixture model. They are compared with log-cumulants of the texture models. The results are adopted to UAVSAR data analysis to determine which model is better for different land types.
Improvement of solenoid magnetic field and its influence on therapeutic effect during magnetic hyperthermia

Magnetic fields have been widely used in the application of bioengineering, and are expected to distribute as uniformly as possible in order to achieve more effective treatment. The solenoid coil is one of the most popular devices used for producing magnetic fields. However it has proved difficult to achieve a uniform profile in a limited length with this approach. This paper proposes an optimization method to improve the uniformity of the magnetic field for a solenoid coil by considering two correcting coils, which are optimized by using a simulated annealing algorithm for its characteristic parameters. The results after the optimization will further be considered in order to analyse the therapeutic effect on a proposed bio-tissue model during magnetic hyperthermia. The magnetic field distribution inside the solenoid is obtained using Maxwell’s theory, and the treatment temperature of the tumor model is determined using Pennes’ bio-heat transfer equation. Simulation results demonstrate that the uniformity of the magnetic field can be significantly improved using the proposed method, and that when considering this optimization, the treatment temperature profile presents a better result compared with a single solenoid.
Little “we’s”: How common identities improve behavior differently for ethnic majority and minority children

This field experiment tested whether inducing common inclusive representations (i.e., one group, dual identity) during contact influences intergroup relations differently for ethnic majority and minority children by changing their metaperceptions and intergroup emotions differently. White (N = 113) and Black (N = 111) 8- to 10-year-old children were exposed to interactive mixed-ethnicity sessions in schools emphasizing either categorization as one group (national group), dual identity (national group with ethnic subgroups), or two ethnic groups. Overall, as predicted, for White children, one-group, but not dual-identity perceptions, improved behavioral intentions by influencing metaperceptions. For Black children, dual-identity, but not one-group, perceptions improved behavioral intentions through metaperceptions. Contrary to the expected, both dual-identity and one-group perceptions were associated with White and Black children’s intergroup emotions.
Multiple pathways to conservation success

Conservation successes can and do happen, however, the process by which society achieves them remains unclear. Using a novel culturomics approach, we analyse word usage within digitized texts to assess the chronological order in which scientists, the public, and policymakers engage in the conservation process for three prominent conservation issues: acid rain in North America, global DDT contamination, and the overexploitation of African elephants for ivory. Variation in the order and magnitude of sector responses among the three issues emphasizes that there are multiple pathways to conservation success and that science is just one component. Our study highlights that while scientists can initiate the process, policy change does not occur in the absence of public interest. We suggest that the fate of conservation action is not solely determined by the scientific soundness of the conservation plan, but rather requires the engagement of scientists, public, and policy makers alike.
A survey on vision-based UAV navigation

Abstract Research on unmanned aerial vehicles (UAV) has been increasingly popular in the past decades, and UAVs have been widely used in industrial inspection, remote sensing for mapping & surveying, rescuing, and so on. Nevertheless, the limited autonomous navigation capability severely hampers the application of UAVs in complex environments, such as GPS-denied areas. Previously, researchers mainly focused on the use of laser or radar sensors for UAV navigation. With the rapid development of computer vision, vision-based methods, which utilize cheaper and more flexible visual sensors, have shown great advantages in the field of UAV navigation. The purpose of this article is to present a comprehensive literature review of the vision-based methods for UAV navigation. Specifically on visual localization and mapping, obstacle avoidance and path planning, which compose the essential parts of visual navigation. Furthermore, throughout this article, we will have an insight into the prospect of the UAV navigation and the challenges to be faced.