Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of polymerase chain reaction and restriction endonuclease analysis for the detection and differentiation of turkey-pox and fowl-pox virus infections

Polymerase chain reaction (PCR) was standardized for the amplification ofA-type inclusion body (ATI) gene using self-designed primers. Amplification was also achieved by using published primer for 39 K core protein gene ofturkeypox virus (TPV) and fowl-pox virus (FPV). Amplicons of 1.8 Kbp and 800 bp product were produced for ATI and 39 K gene, respectively, in both turkey-pox and fowl-pox virus infected samples. The applicability of the standardized PCR for the detection of FPV and TPV in a variety of experimental samples [infected chorioallantoic membrane (CAM), scabs, lymphocytes and chicken embryo fibroblast (CEF) cell cultures] indicated the usefulness ofthis novel technique for the diagnosis of pox virus infection at molecular level. Restriction endonuclease analysis (REA) revealed that the 800 bp amplicon of 39 K gene in both these viruses has no cleavage sites for Bam HI, Hpa II and Eco RI endonuclease enzymes. Bam HI enzyme cleaved FPV ATI gene amplicon at 2 sites giving 3 fragments of 1660, 100 and 40 bp size, but could not cleave TPV amplicon. Hpa II cleaved TPV ATI gene amplicon at 2 sites giving 3 fragments of 1400, 250 and 150 bp but did not cleave that of FPV. The enzyme Eco RI cleaved the ATI gene ampIicon of both the viruses at 2 sites yielding 3 fragments of 1500, 200 and 100 bp in TPV, and 1110, 530 and 160 bp fragments in FPV. The RE analysis revealed the existence of genomic differences in ATI genes of turkey-pox virus and fowl-pox virus.
Lantana: Current Management Status and Future Prospects

Lantana camara L. is a significant weed of which there are some 650 varieties in over 60 countries or island groups. It has been the focus of biological control attempts for a century, yet still poses major problems in many regions. Lantana has a significant impact on economic and environmental areas and is difficult to control. The key to good management of lantana is constant vigilance. Repeated control of new regrowth is critical to success. Control of new infestations should be a priority because the species is able to expand its range during good seasons, but does not die out during poor conditions. This book is a resource for land managers and researchers on methods of lantana control, particularly biocontrol.
Study on the Location of mmWave Antenna for the Autonomous Car’s Detection and Ranging Sensors

The effect of vehicle’s proximity on the radiation pattern when the RADAR’s antenna is mounted on the body of autonomous cars is analysed. Two directional radiation patterns with different specifications are placed at different locations of a realistic car body model. The simulation is performed based on ray-tracing method at 77 GHz, the standard frequency for self-driving applications. It is shown that to obtain a robust RADAR sensor, the antenna radiation pattern is better to have relatively higher gain and lower side-lobe-level (SLL), than narrower half power-beamwidth (HPBW) and higher front-to-back (F/B) ratio. Both academia and industry can benefit from this study.
Efficient Resource Allocation in SCMA-Enabled Device-to-Device Communication for 5G Networks

According to advanced wireless network standards, Device-to-device based communication underlaid conventional cellular network is considered a promising technology to improve the network performance. Precisely, this hybrid architecture provides an efficient resource allocation for cellular and D2D users while increasing the flexible utilization of the spectrum resources. Recently, the sparse code multiple access (SCMA) has been proposed as an efficient non-orthogonal multiple access technology for the 5G network paradigm. The SCMA scheme enhances the spectral efficiency, supports a massive connectivity, and diverses applications by enabling system overloading. Thus, in this paper, SCMA technology is applied to a D2D enabled cellular network, targeted at utilizing the overloading feature of the SCMA scheme to support a massive device connectivity while enhancing the overall network performance. The SCMA scheme is implemented to jointly optimize the codebook and power allocation in the downlink D2D enabled cellular network, with the aim to maximize the system data rate. This joint optimization problem is solved by decomposing the original problem into two sub-problems: codebook allocation and power allocation. For the codebook allocation, the rate aware codebook selection scheme for D2D system (RACBS-D2D) is proposed using conflict graph. For the power allocation solution, a geometric water-filling (GWF) method is utilized to propose the iterative GWF-based power allocation (IGWFPA) scheme. The performance of the proposed schemes is evaluated through simulations that reveal the benefits of the proposed solutions under different scenarios.
Rushed Innovation: Evidence from Drug Licensing

We study the drug licensing behavior (acquisition of rights for developing drugs) of large pharmaceutical firms in the aftermath of large negative shocks to their pipelines, phase 3 failures (P3Fs). We find that P3Fs lead to increased licensing within a year of the event. This result is significant, because one year is a short window given the usual timelines—licensing is a lengthy process that requires extensive planning and careful execution. Supported by a series of additional results, we interpret this finding as a reflection of rushed firm behavior. Correspondingly, our main finding is that drugs licensed in these circumstances (within a year of a P3F event) underperform in subsequent development: they are significantly less likely to reach the market compared with others licensed in normal conditions. Further analysis suggests that this underperformance may stem from the influence of rush on activities taking place in the “last mile” of the licensing process and could hinge on the quality of the agreements that firms converge to during contract negotiations. This paper was accepted by Juanjuan Zhang, marketing.
Thermal Field Analysis for New AlGaN/GaN HEMT With Partial Etched AlGaN Layer

In order to explore the distribution of the device temperature field, this paper takes the new AlGaN/GaN HEMT with partial etched AlGaN layer as the research object. First, the ISE TCAD software is used to simulate the temperature field of AlGaN/GaN HEMT in two dimensions. The simulation results show a decrease of the maximum temperature and average junction temperature in the device channel with shorter thickness of the etched AlGaN layer. As the etching length increases, the hot spot temperature near the gate edge decreases, and the new hot spot position gradually shifts to the drain, which results in a more uniform distribution in the channel. Then, Raman spectroscopy is used to measure the channel junction temperature of AlGaN/GaN HEMTs. The results indicate that when the power dissipation is 0.3W and the etching depth is 5, 10, 15nm, the average channel junction temperature of the new etched AlGaN/GaN HEMT is 9.7%, 17.4% and 30.3% lower than that of the ordinary AlGaN/GaN HEMT, respectively. And the highest temperature of the new AlGaN/GaN HEMT also decreases. We can see that etching the barrier layer of AlGaN/GaN HEMT can not only improve the breakdown voltage, but also effectively reduce the channel junction temperature, and establish the relationship between the high power and thermal stability of the AlGaN/GaN HEMTs.
Steam Vacuuming as a Pre-Evisceration Intervention To Decontaminate Beef Carcasses.

One steam-vacuuming unit (Unit A) was evaluated for removal of visible contamination and reduction of bacterial counts on beef carcass surfaces in five processing plants; a second steam-vacuuming unit (Unit B) was evaluated in two of those same plants at a later date. Experimental treatments included appropriate Controls: steam vacuuming carcass surfaces with or without visible contamination, and knife trimming surfaces with visible contamination. Depending on the processing plant, carcasses were tested on the midline or on the round. Each treatment was applied to a 103-cm2 area of the carcass surface, which was scored for visible contamination and analyzed for aerobic plate counts (APC) at 25°C and for total coliform counts (TCC). Average reductions in APC of 0.57 (Unit A) and 0.72 (Unit B) log CFU/cm2 and in TCC of 0.33 (Unit A) and 0.26 (Unit B) log CFU/cm2 were obtained by steam-vacuuming carcass surfaces which had no visible fecal contamination. Steam vacuuming and knife trimming effectively (P < 0.05) cleaned soiled carcass surfaces and reduced microbial counts. Knife trimming reduced APC and TCC by 1.38 and 1.61 log CFU/cm2 in the Unit A experiment and by 1.64 and 1.72 log CFU/cm2 in the Unit B experiment, respectively. Steam vacuuming carcass surfaces soiled with visible contamination reduced APC and TCC by 1.73 and 1.67 log CFU/cm2 (Unit-A) and by 2.03 and 2.13 log CFU/cm2 (Unit B), respectively. The results of this study suggest that both steam-vacuuming systems available at the time of the study were at least as effective as knife trimming in decontaminating beef carcasses with areas of visible contamination 2.54 cm in the greatest dimension.
How do foreign language teachers motivate students in language learning?

Motivation is one of the keys to success in the language learning process. It is a crucial factor for students in learning a foreign language, and the teachers’ ways to motivate students are also essential. This study aims to investigate language teachers’ ways in motivating students in learning foreign languages. The participants in this study are eight foreign language teachers including English, Arabic, and French teachers. Data were collected through open-ended questionnaires with the teachers. The results of this study showed that most of the foreign language teachers motivated the students in learning a foreign language by sentences (verbal) and this method encouraged students’ instrumental motivation. Next, referring to the time of motivation, four teachers motivated the students at the beginning of each learning process, meanwhile three teachers gave motivations at the beginning and at the end of each learning process. Finally, referring to the types of motivation, only two teachers (i.e. French teachers) could identify motivation types of learners, which are in the form of internal, external, intrinsic, and extrinsic motivation. Meanwhile, other teachers (i.e. English and Arabic teachers), did not mention specifically the names of the motivation types that they knew. To conclude, most of the teachers of this study did not motivate their students maximally in the classrooms. Consequently, this study offers some methods to motivate learners in learning foreign languages, those are the Verbal Method (VM1) and the Visual Method (VM2), and they are further discussed in the paper.
Minimization of IEEE 802.11p Packet Collision Interference through Transmission Time Shifting

V2I communications are characterized by the presence of network nodes in vehicles and in the infrastructures that these vehicles use, as well as by the wireless interactions among them. Safety-related applications demand stringent requirements in terms of latency and packet delivery probability, especially when safety messages have to be delivered to vehicles by the infrastructure. Interference issues stem from the typical characteristics of wireless communications, i.e., the noise of the wireless medium, the limited communication range of the wireless entities, and the receiver passivity of all the conventional wireless transceivers during transmissions. This paper presents a synchronization mechanism to artificially replicate at a host premises destructive interference due to hidden terminals, together with an application-level technique to minimize that interference by shifting the packet transmission time, similarly to the MAC TDMA channel access method. As both have been field-tested, the paper also analyzes the results of these tests, all performed with real hardware on IEEE 802.11p over different frequencies and transmission powers, and with repeatability in mind. The resulting figures attest that interference effects due to hidden terminals may indeed take place on real IEEE 802.11p networks, and that carefully designed time-shifting mechanisms can actively mitigate them.
The fungal holomorph : mitotic, meiotic and pleomorphic speciation in fungal systematics : proceedings of an International Symposium, Newport, Oregon, 4-7 August, 1992

The contents of this book are derived from the National Science Foundation funded working conference of the same title held in Newport, Oregon, USA, 4-7 August 1992. The 32 chapters comprise primary research contributions, reviews and overviews, reports of discussion groups and a summary of the recommendations that were agreed by participants. The scientific information falls into three areas, classical morphological/developmental systematics, molecular systematics and contributions where attempts were made to develop syntheses between the two. Discussion reports concern "The consequences of abandoning the Deuteromycetes" and "How mitotic, meiotic and pleomorphic species could be classified together". Molecular approaches to systematics are increasingly being developed and these can be used to test concepts based on morphological data. This is the first book devoted entirely in mycology to addressing the problems at the interface between the two types of approach. It therefore represents an important addition to the mycological literature, that will also be of interest to taxonomists in other biological disciplines.
EVALUATION OF EPICARDIAL FAT AND CAROTID AND FEMORAL INTIMA-MEDIA THICKNESSES IN GERIATRIC PATIENTS WITH END-STAGE RENAL DISEASE

Introduction: Although atherosclerotic cardiovascular diseases and cardiovascular risks are known to increase in patients with end-stage renal disease, it is not clear whether these risks increase in the geriatric patient population as well. This study aims to evaluate these risks in geriatric patients with end-stage renal disease by evaluating epicardial fat and carotid and femoral intima-media thicknesses, known as markers, for subclinical atherosclerosis and cardiovascular risks.
Market coupling: an empirical study of the Sino-Korean game industry

This study aims to examine the relationship between the Korean and Chinese game industries, and more broadly, the Chinese stock market. Chinese firms are the most important partners and investors in the Korean game industry, which has emerged as a significant component of a thriving Korean economy. The paper examines the impact of growth in the Chinese game industry on the Korean market and the correlation and cointegration between the stock returns of nineteen Korean game companies, the Chinese stock market, and Chinese game companies. A portfolio constructed from Korean game companies listed on the KOSPI and KOSDAQ is analyzed. Variation in the Shanghai Composite Index is shown to significantly influence the performance of Korean game companies. Further, the Korean game industry is sensitive to changes in the stock price of leading Chinese game publishers. The Korean game industry returns more closely mirror the returns of the Chinese stock markets rather than the Korean markets, evidence of the influence of China. As growth and returns in the Korean game industry are closely related to the performance of the Chinese market, future performance is subject to political and economic changes in China.
L-Vector: Neural Label Embedding for Domain Adaptation

We propose a novel neural label embedding (NLE) scheme for the domain adaptation of a deep neural network (DNN) acoustic model with unpaired data samples from source and target domains. With NLE method, we distill the knowledge from a powerful source-domain DNN into a dictionary of label embeddings, or l-vectors, one for each senone class. Each l-vector is a representation of the senone-specific output distributions of the source-domain DNN and is learned to minimize the average L2, Kullback-Leibler (KL) or symmetric KL distance to the output vectors with the same label through simple averaging or standard back-propagation. During adaptation, the l-vectors serve as the soft targets to train the target-domain model with cross-entropy loss. Without parallel data constraint as in the teacher-student learning, NLE is specially suited for the situation where the paired target-domain data cannot be simulated from the source-domain data. We adapt a 6400 hours multi-conditional US English acoustic model to each of the 9 accented English (80 to 830 hours) and kids’ speech (80 hours). NLE achieves up to 14.1% relative word error rate reduction over direct re-training with one-hot labels.
Factors associated with Empathy in Patients with Schizophrenia in Psychiatric Rehabilitation Centers

Purpose: Empathy is the most important communication skill, and patients with schizophrenia in recovery should be taught empathy for vocational rehabilitation and social life. The purpose of this study was to investigate factors affecting empathy, as well as motivation-pleasure and social anhedonia, in patients with schizophrenia in psychiatric rehabilitation. Methods: This study followed a descriptive design using a cross-sectional survey to assess the empathy, social anhedonia, and motivation-pleasure levels of patients with schizophrenia. The participants were 118 patients with schizophrenia from five mental health rehabilitation centers in South Korea. Results: The results of this study show a high correlation among empathy, motivation-pleasure, and social anhedonia. The variables affecting empathy were age, motivation-pleasure, and social anhedonia, and the explanatory power of the variables was 32.6%. Conclusion: The results of this study suggest that improving communication skills and negative symptoms will contribute positively to patients’ social lives and vocational rehabilitation.
ELECTROENCEPHALOGRAM CLASSIFICATION USING VARIOUS ARTIFICIAL NEURAL NETWORKS

Electroencephalography (EEG) is the oldest diagnostic tool used in the field of neurosciences. When a neurologist sees an EEG report, he can point out important neural defects in a person but many a times diagnoses were missed and it is just impossible for human brain to process all the data in EEG. Nowadays many deep machine learning architectures are developed to understand the information contained in EEG signals. This study reviews various literatures on classification of EEG signals using various artificial neural networks like Convoluted neural network, Recurrent Neural Network, Deep Belief neural networks and hybrids.
Benefits of living underground: the case of parasite release in the antlion Myrmeleon timidus

The omnipresence of pathogens makes them a strong selective pressure for most organisms, generating a variety of defensive responses to fight them. One mechanism by which organisms can release this pressure is avoidance of the pathogens in a spatial or temporal context. To date, only a few biological systems provide evidence that habitat selection can favour an escape from pathogens. An abiotic factor that varies across habitats and influences the evolution of host life history is humidity, which correlates positively with pathogen levels in the environment. Entomopathogenic fungi are abundant in soils and are obligate killers that require humidity for host infection. Antlions (Neuroptera: Myrmeleontidae) are typical soil‐dwelling insects that can live several years as larvae, buried in dry and fine substrates where they build their traps. This lifestyle may release them from selective pressure by entomopathogenic fungi. Here, we investigated whether living underground provides protection against the generalist entomopathogenic fungus Beauveria bassiana (Bals.‐Criv.) Vuill. in the antlion Myrmeleon timidus Gerstaecker under low or high humidity in the environment. Individuals that were inoculated with the fungus showed greater survival rates when buried in dry sand compared to individuals that were kept half‐buried or without sand, with similar outcomes across humidity levels. Given that the diversity of antlions is higher in arid environments, this benefit obtained from pit‐building behaviour seems to be a coincidental by‐product of this foraging strategy, which would be particularly beneficial in environments where fungal pathogens are common.
Machine Learning Neuroprotective Strategy Reveals a Unique Set of Parkinson Therapeutic Nicotine Analogs

Aims: Present a novel machine learning computational strategy to predict the neuroprotection potential of nicotine analogs acting over the behavior of unpaired signaling pathways in Parkinson’s disease. Background: Dopaminergic replacement has been used for Parkinson’s Disease (PD) treatment with positive effects on motor symptomatology but low progression and prevention effects. Epidemiological studies have shown that nicotine consumption decreases PD prevalence through neuroprotective mechanisms activation associated with the overstimulation of signaling pathways (SP) such as PI3K/AKT through nicotinic acetylcholine receptors (e.g α7 nAChRs) and over-expression of anti-apoptotic genes such as Bcl-2. Nicotine analogs with similar neuroprotective activity but decreased secondary effects remain as a promissory field. Objective: The objective of this study is to develop an interdisciplinary computational strategy predicting the neuroprotective activity of a series of 8 novel nicotine analogs over Parkinson’s disease. Methods: We present a computational strategy integrating structural bioinformatics, SP manual reconstruction, and deep learning to predict the potential neuroprotective activity of 8 novel nicotine analogs over the behavior of PI3K/AKT. We performed a protein-ligand analysis between nicotine analogs and α7 nAChRs receptor using geometrical conformers, physicochemical characterization of the analogs and developed manually curated neuroprotective datasets to analyze their potential activity. Additionally, we developed a predictive machine-learning model for neuroprotection in PD through the integration of Markov Chain Monte-Carlo transition matrix for the 2 SP with synthetic training datasets of the physicochemical properties and structural dataset. Results: Our model was able to predict the potential neuroprotective activity of seven new nicotine analogs based on the binomial Bcl-2 response regulated by the activation of PI3K/AKT. Conclusion: Hereby, we present a robust novel strategy to assess the neuroprotective potential of biomolecules based on SP architecture. Our theoretical strategy can be further applied to the study of new treatments related to SP deregulation and may ultimately offer new opportunities for therapeutic interventions in neurodegenerative diseases.
Sequence analysis of theChlamydomonas reinhardtii flagellar a dynein gene

Flagellar outer row dynein ATPases have been used extensively as model systems for studies of microtubule-based motility. Previously full-length sequences were only available for two of the three catalytic heavy-chain subunits (DHCs) of this enzyme. We have completed the sequence of an 18-kb genomic region encoding the Chlamydomonas reinhardtii flagellar outer row dynein alpha heavy chain. Unlike the beta- and gamma-subunits, DHC alpha is not required for assembly of other outer row dynein proteins, except for a tightly associated light chain, and thus occupies a unique position within this enzyme complex. The predicted 4,499 residue protein retains sequence homology to other dynein heavy chains throughout its central and C-terminal regions but lacks homology to any other dyneins in the first 1,000 amino acids, which may account for its unusual assembly properties. This N-terminal domain of DHC alpha contains a repetitive sequence rich in alanines, prolines, and glutamic acids. Within the more homologous C-terminal region, which includes the catalytic domain, three short sequences unique to DHC alpha may account for its specific catalytic properties and in vivo phosphorylation pattern.