Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of a longitudinal ordinal response clinical trial using dynamic models

Summary. In many areas of pharmaceutical research, there has been increasing use of categorical data and more specifically ordinal responses. In many cases, complex models are required to account for different types of dependences among the responses. The clinical trial that is considered here involved patients who were required to remain in a particular state to enable the doctors to examine their heart. The aim of this trial was to study the relationship between the dose of the drug administered and the time that was spent by the patient in the state permitting examination. The patient's state was measured every second by a continuous Doppler signal which was categorized by the doctors into one of four ordered categories. Hence, the response consisted of repeated ordinal series. These series were of different lengths because the drug effect wore off faster (or slower) on certain patients depending on the drug dose administered and the infusion rate, and therefore the length of drug administration. A general method for generating new ordinal distributions is presented which is sufficiently flexible to handle unbalanced ordinal repeated measurements. It consists of obtaining a cumulative mixture distribution from a Laplace transform and introducing into it the integrated intensity of a binary logistic, continuation ratio or proportional odds model. Then, a multivariate distribution is constructed by a procedure that is similar to the updating process of the Kalman filter. Several types of history dependences are proposed.
Changes of natural compounds of Artemisia annua L. by methyl jasmonate and silver nanoparticles

Artemisia annua L. (Asteraceae) is a traditional medicinal herb whose natural compounds have crucial role in its defense system. Production of these antifungal and antimicrobial compounds can be induced by certain elicitors. In the present research the plants in their flowering stage were treated with two well-known elicitors i.e., silver nanoparticles (AgNPs) and methyl Jasmonate (MeJA), both of which provoke defense responses. The treatments were conducted at final concentrations of 0.4, 0.8 and 1.2 mM of AgNPs and 50 and 100 µM of MeJA for 24 h. The content of natural compounds e.g., anthocyanin, flavonoids, and essential oils as well as radical scavenging activity and membrane lipid peroxidation rate were determined. Treatment of the plants with MeJA and AgNPs increased anthocyanin content, although not efficient to reduce peroxidation of membrane lipids. Total of 15 components were identified as essential oil of the plants with or without treatment with MeJA and AgNPs. High content of Camphor was observed in those plants treated with 1.2 mM AgNPs (6.61%). The most value of Germacrene-D and trans–caryophelene were observed in plants treated with 50µm and 100µm MeJA (11.02% and 9.67%). The high concentration of β-selinene (23.02%) and Artemisia ketone (9.68%) were observed in treatment with AgNPs. Treatment with 1.2mM AgNPs and 50 µM MeJA resulted in remarkable increase of oxygenated monoterpenes. The results suggested that high concentrations of AgNPs and MeJA hindered biosynthesis of longer terpenoids so that monoterpens were more abundant than sesquiterpens in treated plants, compared to nontreated ones.
DEVELOPMENT OF KNOWLEDGE OF THE TAXONOMY AND PHYLOGENY OF LIVING ORGANISMS FOR FUTURE BIOLOGY TEACHERS

The science does not operate with the only recognized scheme representing the taxonomy of living organisms. Each version of it is temporary employed. We offer the schoollevel curriculum to include t he system of two domains (Prokaryotes and Eukaryotes) and seven kingdoms (Viruses, Bacteria, Archaea, Protista, Plants, Fungi, Animals). Further research can be focused on the improvement of the scheme of living organisms due to the recent advances in the molecular branches of eukaryotes on the phylogenetic tree (Amoebozoa, Opisthokonta, Archaeplastida, Excavata, supergroup SAR); evolution factors (horizontal gene transfer and symbiogenesis). It should also take into account the schoollevel curricula, pupils' age and tutor's
Critical snow density threshold for Dall’s sheep (Ovis dalli dalli)

Snow cover can significantly impact animal movement and energetics, yet few studies have investigated the link between physical properties of snow and energetic costs. Quantification of thresholds in snow properties that influence animal movement are needed to help address this knowledge gap. Recent population declines of Dall’s sheep (Ovis dalli dalli Nelson, 1884) could be due in part to changing snow conditions. We examined the effect of snow density, snow depth, and snow hardness on sinking depths of Dall’s sheep tracks encountered in Wrangell–St. Elias National Park and Preserve, Alaska. Snow depth was a poor predictor of sinking depths of sheep tracks (R2 = 0.02, p = 0.38), as was mean weighted hardness (R2 = 0.09, p = 0.07). Across competing models, top layer snow density (0–10 cm) and sheep age class were the best predictors of track sink depths (R2 = 0.58). Track sink depth decreased with increasing snow density, and the snowpack supported the mass of a sheep above a density threshold of 329 ± 18 kg/m3 (mean ± SE). This threshold could aid interpretation of winter movement and energetic costs by animals, thus improving our ability to predict consequences of changing snowpack conditions on wildlife.
Towards Intelligent Systems for Colonoscopy

Colorectal cancer is one of the leading causes of cancer related deaths. Colorectal cancer’s survival rate depends on the stage in which it is detected, decreasing from rates higher than 95% in the first stages to rates lower than 35% in stages IV and V (Tresca, A. (2010)); hence the importance of detecting it on its early stages by using screening techniques, such as colonoscopy (Hassinger, J.P., Holubar, S.D. et al. (2010)), which is still considered the gold standard for the screening of patients for colon cancers and lesions. Classical focal colonoscopy has been proved to be a successful tool for colon screening, although other tools are being also used for this purpose, such as Virtual Colonoscopy, Computed Tomography Colonoscopy, Chromoendoscopy or Wireless Capsule Video Endoscopy, among others. In this chapter we present tools that can be used to build intelligent systems for colonoscopy. The idea is, by using methods based on computer vision and artificial intelligence, add significant value to the colonoscopy procedure. Intelligent systems are being used to assist in other medical interventions. For instance, we can build systems that can be used to develop the knowledge bases used by expert systems, such as KARDIO (Bratko et al. (1990), which was developed to interpret electrocardiograms. Another example can consist of developing a system that, in the context of anesthesia, provides a robust/reliable control system that could determine the optimal infusion rate of the drugs (muscle relaxant, anesthetic, and analgesic) simultaneously, and titrate each drug in accordance to its effects and interactions. Such a system would be a valuable assistant to the anesthetist in the operating theater. An example of such a system can be found in the work of Nunes et al. (2005). More close to our topic of interest, colonoscopy, we can find many examples of intelligent systems build to assist in cancer detection. Such is the case of breast cancer detection (Wei et al. (2011)) or prostate cancer detection (Viswanath et al. (2011)). The question that arises now is: how can intelligent systems help in colonoscopy? What kind of applications these systems can be built for? In Figure 1 we depict some of the potential areas related to colonoscopy where an intelligent system can play a key role. As shown in Figure 1, we foresee four different areas where an intelligent system can be introduced and add significant value to the colonoscopy procedure:
A Teacher Student Network For Faster Video Classification

Over the past few years, various tasks involving videos such as classification, description, summarization and question answering have received a lot of attention. Current models for these tasks compute an encoding of the video by treating it as a sequence of images and going over every image in the sequence, which becomes computationally expensive for longer videos. In this paper, we focus on the task of video classification and aim to reduce the computational cost by using the idea of distillation. Specifically, we propose a Teacher-Student network wherein the teacher looks at all the frames in the video but the student looks at only a small fraction of the frames in the video. The idea is to then train the student to minimize (i) the difference between the final representation computed by the student and the teacher and/or (ii) the difference between the distributions predicted by the teacher and the student. This smaller student network which involves fewer computations but still learns to mimic the teacher can then be employed at inference time for video classification. We experiment with the YouTube-8M dataset and show that the proposed student network can reduce the inference time by upto 30% with a negligent drop in the performance.
Growth response of wheat cultivars to bacterial inoculation in calcareous soil

In this study the plant growth-promoting bacteria were analysed for their growth-stimulating effects on two wheat cultivars. The investigations were carried out in pot experiments using calcareous soil. The results showed that bac terial strains Pseudomonas spp. NUU1 and P. fluorescens NUU2 were able to colonize the rhizosphere of both wheat cultivars. Their plant growth-stimulating abilities were affected by wheat cultivars. The bacterial strains Pseudomonas sp. NUU1 and P. fluorescens NUU2 significantly stimulated the shoot and root length and dry weight of wheat cv. Turon, whereas cv. Residence was less affected by bacterial inoculation. The results of our study suggest that inoculation of wheat with Pseudomonas strains can improve plant growth in calcareous soil and it depends upon wheat cultivars. Prior to a selection of good bacterial inoculants, it is recommended to select cultivars that benefit from association with these bacteria.
Theoretical modeling of resonant laser excitation of atoms in a magnetic field

The interaction of near-resonant laser radiation with atoms immersed in a magnetic B field is calculated using a quantum electrodynamic model. In this model, the magnetic field is assumed to produce a small perturbation such that the degeneracy of the magnetic substates is lifted while maintaining the usual quantum numbers that define the states (the Zeeman effect). The laser radiation is considered to have a narrow bandwidth and to be temporally and spatially coherent. The model produces three general coupled differential equations that describe the state populations and their relative coherences and the optical coherences between levels coupled by the laser radiation. The model can therefore be directly applied to different experiments ranging from atom trapping and cooling experiments through to collision experiments carried out in magnetic and laser fields.
Classification Of Computer Generated Images From Photographic Images Using Convolutional Neural Networks

This paper proposes a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a new convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, CNN will learn features based on an image's content instead of the structural features of the image. The new layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images and it was concluded that it performs better than the current state of the art methods.
Iterative Detection using MMSE-PIC Demapping for MIMO-GFDM Systems

Diverse requirements are foreseen for the 5G cellular system and new waveforms are being researched for the physical layer (PHY), where the non-orthogonal Generalized Frequency Division Multiplexing (GFDM) is one candidate. Its inherent self-interference makes receiver design challenging, particularly when besides inter-carrier interference (ICI) and inter-symbol interference (ISI) also inter-antenna interference (IAI) occurs, as in systems that employ spatial multiplexing (SM) to increase the throughput. To encounter this interference, we apply the prominent minimum mean squared error with parallel interference cancellation (MMSE-PIC) iterative receiver structure to GFDM, and provide a formulation that is suitable for a low-complexity implementation. We analyze the decoding performance employing a well-known current WiMax LDPC code. The proposed demapping algorithm can be implemented with complexity that scales linearly with the number of subcarriers of the system. Analysis of information transfer characteristics shows that the MMSE-PIC demapper for GFDM exhibits potential to outperform the OFDM demapper with a matching code, however, simulations of frame error rate (FER) show inferior performance of GFDM. These results emphasize the importance of a joint waveform and code design in order to exploit the full potential of the MMSE-PIC receiver structure for GFDM.
Identification of Average Treatment Effects in Social Experiments Under Alternative Forms of Attrition

As any empirical method used for causal analysis, social experiments are prone to attrition which may flaw the validity of the results. This article considers the problem of partially missing outcomes in experiments. First, it systematically reveals under which forms of attrition—in terms of its relation to observable and/or unobservable factors—experiments do (not) yield causal parameters. Second, it shows how the various forms of attrition can be controlled for by different methods of inverse probability weighting (IPW) that are tailored to the specific missing data problem at hand. In particular, it discusses IPW methods that incorporate instrumental variables (IVs) when attrition is related to unobservables, which has been widely ignored in the experimental literature before.
On the non-detection of γ-rays from energetic millisecond pulsars – dependence on viewing geometry

Millisecond pulsars (MSPs) and normal non-recycled pulsars are both detected in γ-rays. However, it appears that a much larger fraction of known energetic and nearby MSPs are detected in γ-rays, in comparison with normal pulsars, thereby making undetected γ-ray MSPs exceptions. In this paper, we demonstrate that the viewing angles (i.e. between the pulsar spin axis and the line of sight) are well described by the orbital inclination angles which, for binary MSPs with helium white dwarf companions, can be determined using the relationship between the orbital period and the white dwarf mass. We use the predicted viewing angles, in complement with values obtained from other constraints when available, to identify the causes of non-detection of energetic and nearby MSPs from the point of view of beaming geometry and orientation. We find evidence for slightly different viewing angle distributions, and postulate that energetic and nearby MSPs are mainly undetected in γ-rays simply because they are seen under unfavourable (i.e. small) viewing angles. We finally discuss the magnetic fields of γ-ray detected pulsars and show that pulsars which are efficient at converting their rotational energy into γ-ray emission may have overestimated dipolar magnetic field strengths.
Intraspecific variation among isolates of the entomopathogenic nematode Steinernema feltiae from Bull Island, Ireland

The application of large numbers of entomopathogenic nematodes (EPN) to control insect pests of agriculture is likely to have an impact on the local EPN fauna, yet little is known about the intraspecific relationships between EPN populations, particularly with regard to phylogeny and outbreeding. Here we assess the fitness, with regards to fecundity, host insect mortality and time taken to produce progeny, of isolates of Steinernema feltiae from Bull Island, Ireland. Exon-primed, intron-crossing (EPIC) PCR was used to examine intraspecific phylogenies between S. feltiae isolates, and identified up to three possible colonisation events of Bull Island. EPIC-PCR grouped two isolates, 33.D. (2) and 59.F. (2), separately from the remaining ten S. feltiae isolates These same two isolates consistently performed poorly in all fitness assessments. Following the crossbreeding of all isolates in Galleria mellonella , the number of host cadavers exhibiting emerging infective juveniles was significantly fewer than expected and there were significant differences between isolates in the number of days until progeny were observed. Host insect mortality varied between 40 and 87%. Such intraspecific variation may be a result of adaptation to different microhabitats of Bull Island, which in turn may be accentuated by laboratory culture practices.
Estimation for Spectral Image Reconstruction Using 3-band Image and Multipoint Spectral Measurements

This paper presents a new spectral image reconstruction method based on MAP estimation from a 3-band image and multipoint spectral measurements. Spectral information is utilized as auxiliary information to improve the accuracy of spectral reflectance estimation from 3-band images. As a result of the preliminary experiment, it is shown that the proposed method with 81 spectral measurements reduces the color estimation error in CIELAB by about half compared to the conventional Wiener estimation method.
Substrate oxidation in female adults during endurance exercise throughout menstrual cycle phases: IronFEMME pilot study

The main aim of the study was to investigate the effect of menstrual cycle phases on substrate oxidation during steady state intensity exercise in adult females with regular menstrual cycle and on oral contraceptive (OC). Twenty-four healthy endurance and strength trained females, with regular menstrual cycle phases (n= 15; Age 35.6±4.2; height 163.9±5.9 cm; body mass 58.1±5.2 kg; VO2peak 50.3±3.6 ml·min-1·kg-1) or on oral contraceptives (n=9; Age 30.4±4.5; height 163.9±9.0 cm; body mass 58.1±6.7 kg; VO2peak 52.4±4.2 ml·min-1·kg-1) participated in the study. All participants performed a graded maximal exercise test to determine their peak oxygen consumption (VO2peak). Participants then exercised at the speed corresponding to 75% of VO2peak for 40 minutes on a treadmill in each menstrual cycle phase: regular menstrual cycle group (early follicular phase, mid-follicular phase and luteal phase) and OC group (hormonal phase and non-hormonal phase). There were no differences in the respiratory exchange ratio of each phase, in regular menstrual cycle phase group (mean±SEM): early-follicular phase 0.89±0.01, mid-follicular phase 0.87±0.01 and luteal phase 0.88±0.01 (p>0.05). There were also no differences in respiratory exchange ratio for the participants using oral contraceptive: hormonal phase 0.89±0.01 and non-hormonal phase 0.91±0.01 (p>0.05). However, we found that OC may influence fat oxidation (p=0.018) during the hormonal phase. Our preliminary results suggest that menstrual cycle and oral contraceptive do not influence substrate oxidation in females with regular menstrual cycle phases. Regarding the few disparities, more research is needed to understand how sexual hormones influence substrate oxidation in female.
Focus on Meiosis Cytoskeleton and cell cycle control during meiotic maturation of the mouse oocyte: integrating time and space

During meiotic maturation of mammalian oocytes, two successive divisions occur without an intermediate phase of DNA replication, so that haploid gametes are produced. Moreover, these two divisions are asymmetric, to ensure that most of the maternal stores are retained within the oocyte. This leads to the formation of daughter cells with different sizes: the large oocyte and the small polar bodies. All these events are dependent upon the dynamic changes in the organization of the oocyte cytoskeleton (microtubules and microfilaments) and are highly regulated in time and space. We review here the current knowledge of the interplay between the cytoskeleton and the cell cycle machinery in mouse oocytes, with an emphasis on the two major activities that control meiotic maturation in vertebrates, MPF (Maturation promoting factor) and CSF (Cytostatic factor).
A Maturity Model for Business Model Management in Industry 4 . 0

In a continuously changing business environment and the era of digitalization, business models need to adapt constantly to allow organizations to differentiate themselves from their competitors and to secure their economic survival. However, organizations are neither able to review their business model management nor systemize it productively. Hence, the combination of Industry 4.0, business model and business model management aspects emphasizes an organization’s potential and results in an increased competitive and operational success. To guide an organization’s advancement, a maturity model for business model management is developed, which delivers assistance suitable to an organization’s requirements and strategic orientation. It assesses the organization’s current maturity level and proposes sequential steps to advance towards a refined business model and process mastery by indicating improvement potentials. Thus, the maturity model links an organization’s existing organizational and operational knowledge to new concepts and makes it accessible through a modified business model for Industry 4.0.
Measurement of Salespeople's Job Satisfaction: Convergent and Discriminant Validity of Corresponding INDSALES and Job Descriptive Index Scales

The satisfaction scales for work, coworkers, supervision, pay, and promotion of the INDSALES and Job Descriptive Index (JDI) were obtained from a national sample of 209 salesmen in the health care industry. Convergent and discriminant validity were examined by using the criteria of Campbell and Fiske.
Feature Extraction Methods for Studying Surface Electromyography and Kinematic Measurements in Parkinson’s Disease

Parkinson’s disease is a progressive neurodegenerative disease that affects 1 % of people over 60 years of age [9]. In PD, there is a dopaminergic neuronal loss in the substantia nigra in the basal ganglia of the cerebra [48]. It has been observed that the basal ganglia has a specific effect on the temporal organization of motor cortical activity during muscle contractions. In this way, the dysfunction of the basal gangliamay lead tomotor symptoms of PD. [37] The primary symptoms of PD include tremor, muscle rigidity and slowness of movements. The diagnosis is based on the presence of the primary symptoms and on the response to medication. [17, 18]. However, the diagnosis can be problematic. Clinicopathological studies from the UK and Canada have shown that the disease is diagnosed incorrectly in about 25 % of patients [48]. The pre-motor period before diagnosis may be long (5–20 years) and at the time of the diagnosis already 50–60 % of the dopaminergic neurons may be lost [22, 38].