Miracle-dz/UniFAR-FTUs huggingface dataset:
An Assessment of Puku (Kobus vardonii) Populations in Kafue National Park, Zambia Using Ground Transects Other than the Road Network

Abstract In the past, ground counts in Kafue National Park (KNP) were predominantly confined to the road network owing to the vastness of the Park. Though essential information was yielded, results could not be generalized for the entire area as the road network did not traverse all habitats. Thus, using Distance Sampling methods, an attempt was made in 2010 to obtain unbiased and precise estimates of puku population and structure. Puku was chosen, because it acted as an indicator species for the SEED Programme and secondly its distribution during the dry season was predominantly confined to areas that were relatively accessible. The study area was defined using dry season distributions obtained from daily patrol data and from previous aerial survey reports. With an effort of 152.74km, 90 observations were yielded in groups ranging from 1–76 individuals with a modal size of one. This remained consistent with other studies that have shown that puku usually occur in small groups. Age ratios indicated that there were significantly more adults (81.7%) than sub-adults and juveniles together (18.3%), and may well be a concern to management. Sex ratios were more skewed towards the females, a norm for wild populations. Density estimates (0.433, CV = ± 24.7%) fell within the upper limit of the 2008 aerial count estimate (0.329/km2). Together, these results suggest that Distance Sampling using transects rather than the road network is a more useful and effective technique for estimating densities of puku and should in future be extended to incorporate other large mammals.
Educational Technologies in Problem-Based Learning in Health Sciences Education: A Systematic Review

Background As a modern pedagogical philosophy, problem-based learning (PBL) is increasingly being recognized as a major research area in student learning and pedagogical innovation in health sciences education. A new area of research interest has been the role of emerging educational technologies in PBL. Although this field is growing, no systematic reviews of studies of the usage and effects of educational technologies in PBL in health sciences education have been conducted to date. Objective The aim of this paper is to review new and emerging educational technologies in problem-based curricula, with a specific focus on 3 cognate clinical disciplines: medicine, dentistry, and speech and hearing sciences. Analysis of the studies reviewed focused on the effects of educational technologies in PBL contexts while addressing the particular issue of scaffolding of student learning. Methods A comprehensive computerized database search of full-text articles published in English from 1996 to 2014 was carried out using 3 databases: ProQuest, Scopus, and EBSCOhost. Eligibility criteria for selection of studies for review were also determined in light of the population, intervention, comparison, and outcomes (PICO) guidelines. The population was limited to postsecondary education, specifically in dentistry, medicine, and speech and hearing sciences, in which PBL was the key educational pedagogy and curriculum design. Three types of educational technologies were identified as interventions used to support student inquiry: learning software and digital learning objects; interactive whiteboards (IWBs) and plasma screens; and learning management systems (LMSs). Results Of 470 studies, 28 were selected for analysis. Most studies examined the effects of learning software and digital learning objects (n=20) with integration of IWB (n=5) and LMS (n=3) for PBL receiving relatively less attention. The educational technologies examined in these studies were seen as potentially fit for problem-based health sciences education. Positive outcomes for student learning included providing rich, authentic problems and/or case contexts for learning; supporting student development of medical expertise through the accessing and structuring of expert knowledge and skills; making disciplinary thinking and strategies explicit; providing a platform to elicit articulation, collaboration, and reflection; and reducing perceived cognitive load. Limitations included cumbersome scenarios, infrastructure requirements, and the need for staff and student support in light of the technological demands of new affordances. Conclusions This literature review demonstrates the generally positive effect of educational technologies in PBL. Further research into the various applications of educational technology in PBL curricula is needed to fully realize its potential to enhance problem-based approaches in health sciences education.
Same-Patient Reproducibility of State Entropy: A Comparison of Simultaneous Bilateral Measurements During General Anesthesia

BACKGROUND: State Entropy® (SE) is an index of anesthetic depth similar to Bispectral Index® (BIS). Both indices use a single-channel electroencephalogram, recorded from a unilaterally applied electrode on the forehead, as their input. Intrapatient reproducibility of BIS was questioned in a recent study in which simultaneous measurements from two electrodes applied to the same patient showed conflicting anesthetic depths. Our purpose was to determine whether SE results are similarly reproducible, even though their computation uses a different algorithm than BIS. In this study, we investigated the reproducibility of SE measurements simultaneously obtained from bilaterally applied electrodes in the same patient. METHODS: Entropy electrodes were applied bilaterally on 21 patients under general inhaled anesthesia. Simultaneous SE measurements from both electrodes were recorded every 10 s from each patient. Data were analyzed with Bland-Altman statistics. RESULTS: We obtained 14,379 pairs of SE measurements. Four percent of the individual measurements suggested conflicting anesthetic depth along with a numeric difference more than 10 points. Bias was not clinically significant (−0.3). Ninety-five percent limits of agreement were −11.7 and +11.6. CONCLUSIONS: SE showed a clinically significant degree of disagreement when probes were applied on both sides of the forehead in the same patient. Bland-Altman statistics showed better same-patient reproducibility in SE than did a similar study on BIS. Nevertheless, 4% of the simultaneously measured pairs of SE suggested different anesthetic depths and differed by more than 10 points. Caution is advised when using SE as a clinical index of anesthetic depth.
Silibinin strongly inhibits the growth kinetics of colon cancer stem cell-enriched spheroids by modulating interleukin 4/6-mediated survival signals

Involvement of cancer stem cells (CSC) in initiation, progression, relapse, and therapy-resistance of colorectal cancer (CRC) warrants search for small molecules as ‘adjunct-therapy’ to target both colon CSC and bulk tumor population. Herein, we assessed the potential of silibinin to eradicate colon CSC together with associated molecular mechanisms. In studies examining how silibinin modulates dynamics of CSC spheroids in terms of its effect on kinetics of CSC spheroids generated in presence of mitogenic and interleukin (IL)-mediated signaling which provides an autocrine/paracrine amplification loop in CRC, silibinin strongly decreased colon CSC pool together with cell survival of bulk tumor cells. Silibinin effect on colon CSC was mediated via blocking of pro-tumorigenic signaling, notably IL-4/-6 signaling that affects CSC population. These silibinin effects were associated with decreased mRNA and protein levels of various CSC-associated transcription factors, signaling molecules and markers. Furthermore, 2D and 3D differentiation assays indicated formation of more differentiated clones by silibinin. These results highlight silibinin potential to interfere with kinetics of CSC pool by shifting CSC cell division to asymmetric type via targeting various signals associated with the survival and multiplication of colon CSC pool. Together, our findings further support clinical usefulness of silibinin in CRC intervention and therapy.
Nested Periodic Matrices and Dictionaries: New Signal Representations for Period Estimation

In this paper, we propose a new class of techniques to identify periodicities in data. We target the period estimation directly rather than inferring the period from the signal's spectrum. By doing so, we obtain several advantages over the traditional spectrum estimation techniques such as DFT and MUSIC. Apart from estimating the unknown period of a signal, we search for finer periodic structure within the given signal. For instance, it might be possible that the given periodic signal was actually a sum of signals with much smaller periods. For example, adding signals with periods 3, 7, and 11 can give rise to a period 231 signal. We propose methods to identify these “hidden periods” 3, 7, and 11. We first propose a new family of square matrices called Nested Periodic Matrices (NPMs), having several useful properties in the context of periodicity. These include the DFT, Walsh-Hadamard, and Ramanujan periodicity transform matrices as examples. Based on these matrices, we develop high dimensional dictionary representations for periodic signals. Various optimization problems can be formulated to identify the periods of signals from such representations. We propose an approach based on finding the least l2 norm solution to an under-determined linear system. Alternatively, the period identification problem can also be formulated as a sparse vector recovery problem and we show that by a slight modification to the usual l1 norm minimization techniques, we can incorporate a number of new and computationally simple dictionaries.
Polymeric ionic liquids for CO2 capture and separation: potential, progress and challenges

The increasing level of carbon dioxide (CO2) in the atmosphere is a big threat to the environment and plays a key role towards global warming and climate change. In this context to combat such issues, polymeric ionic liquids (PILs) serve as potential substitutes that offer an extremely versatile and tunable platform to fabricate a wide variety of sorbents for CO2 capture, in particular, for flue gas separation (CO2/N2) and natural gas purification (CO2/CH4). Formerly, there have been several reports on exploitation of ionic liquids for CO2 sorption with promising results. However, just a few have focused on polymeric ionic liquids which significantly over-performed the sorption efficiency of the molecular ionic liquids. This review is first ever of its kind which showcases the potential of PILs as a new member of the CO2 adsorbent family. The most dynamic aspect of PILs research at present is the curiosity to explore their potential as solid sorbents for CO2 capture and separation. This review not only highlights the recent advances in the area of PILs as sorbents for CO2 uptake but also portrays the forthcoming challenges in improving their efficiency. The effect of various cations, anions, polymer backbones, alkyl substituents, porosity, cross-linking, molecular weight and moisture on the CO2 sorption capacity and separating efficiency is scrutinized in detail. Moreover, future strategies to increase the CO2 capture performance of PILs are also discussed.
Relevance Feedback Models for Recommendation

We extended language modeling approaches in information retrieval (IR) to combine collaborative filtering (CF) and content-based filtering (CBF). Our approach is based on the analogy between IR and CF, especially between CF and relevance feedback (RF). Both CF and RF exploit users' preference/relevance judgments to recommend items. We first introduce a multinomial model that combines CF and CBF in a language modeling framework. We then generalize the model to another multinomial model that approximates the Polya distribution. This generalized model outperforms the multinomial model by 3.4% for CBF and 17.4% for CF in recommending English Wikipedia articles. The performance of the generalized model for three different datasets was comparable to that of a state-of-the-art item-based CF method.
Amniotic Mesenchymal Tissue Cells Inhibit Dendritic Cell Differentiation of Peripheral Blood and Amnion Resident Monocytes

Cells derived from the amniotic membranes of human term placenta have drawn much interest for their characteristics of multipotency and low immunogenicity, supporting a variety of possible clinical applications in the field of cell transplantation and regenerative medicine. We have previously shown that cells derived from the mesenchymal region of human amnion (AMTC) can strongly inhibit T-lymphocyte proliferation. In this study, we demonstrate that AMTC can block differentiation and maturation of monocytes into dendritic cells (DC), preventing the expression of the DC marker CD1a and reducing the expression of HLA-DR, CD80, and CD83. The monocyte maturation block resulted in impaired allostimulatory ability of these cells on allogeneic T cells. In attempting to define the mechanisms responsible for these findings, we have observed that the presence of AMTC in differentiating DC cultures results in the arrest of the cells to the G0 phase and abolishes the production of inflammatory cytokines such as TNF-α, CXCL10, CXCL9, and CCL5. Finally, we also demonstrate that the monocytic cells present in the amniotic mesenchymal region fail to differentiate toward the DC lineage. Taken together, our data suggest that the mechanisms by which AMTC exert immumodulatory effects do not only relate directly to T cells, but also include inhibition of the generation and maturation of antigen-presenting cells. In this context, AMTC represent a very attractive source of multipotent allogeneic cells that promise to be remarkably valuable for cell transplantation approaches, not only due to their low immunogenicity, but also because of the added potential of modulating immune responses, which could be fundamental both for controlling graft rejection after transplantation and also for controlling diseases characterized by inflammatory processes.
Glycoproteins of coated pits, cell junctions, and the entire cell surface revealed by monoclonal antibodies and immunoelectron microscopy

Topographical descriptions of three major plasma membrane glycoproteins of murine 3T3 cells were obtained by immunoelectron microscopy with monoclonal antibodies. A glycoprotein of Mr 80,000 was distributed throughout the total cell surface. A second of Mr 90,000 was concentrated in coated pits, and a third of Mr 100,000 was localized at cell junctions.
DSP-Based Cross-Coupled Synchronous Control for Dual Linear Motors via Intelligent Complementary Sliding Mode Control

A digital signal processor (DSP)-based cross-coupled intelligent complementary sliding mode control (ICSMC) system is proposed in this paper for the synchronous control of a dual linear motor servo system. The dual linear motor servo system with two parallel permanent magnet linear synchronous motors is installed in a gantry position stage. The dynamic model of single-axis motion control system with a lumped uncertainty, which comprises parameter variations, external disturbances, and nonlinear friction force, is introduced first. Then, to achieve an accurate trajectory tracking performance with robustness, a cross-coupled ICSMC is developed. In this approach, a Takagi-Sugeno-Kang-type fuzzy neural network estimator with accurate approximation capability is implemented to estimate the lumped uncertainty. Moreover, since a cross-coupled technology is incorporated into the proposed intelligent control scheme for the gantry position stage, both the position tracking and synchronous errors of the dual linear motors will simultaneously converge to zero. Furthermore, to effectively demonstrate the control performance of the proposed intelligent control approach, a 32-b floating-point DSP-based control computer is developed for the implementation of the proposed cross-coupled ICSMC system. Finally, some experimental results are illustrated to show the validity of the proposed control approach.
A Microsaccadic Rhythm Modulates Gamma-Band Synchronization and Behavior

Rhythms occur both in neuronal activity and in behavior. Behavioral rhythms abound at frequencies at or below 10 Hz. Neuronal rhythms cover a very wide frequency range, and the phase of neuronal low-frequency rhythms often rhythmically modulates the strength of higher-frequency rhythms, particularly of gamma-band synchronization (GBS). Here, we study stimulus-induced GBS in awake monkey areas V1 and V4 in relation to a specific form of spontaneous behavior, namely microsaccades (MSs), small fixational eye movements. We found that MSs occur rhythmically at a frequency of ∼3.3 Hz. The rhythmic MSs were predicted by the phase of the 3.3 Hz rhythm in V1 and V4 local field potentials. In turn, the MSs modulated both visually induced GBS and the speed of visually triggered behavioral responses. Fast/slow responses were preceded by a specific temporal pattern of MSs. These MS patterns induced perturbations in GBS that in turn explained variability in behavioral response speed. We hypothesize that the 3.3 Hz rhythm structures the sampling and exploration of the environment through building and breaking neuronal ensembles synchronized in the gamma-frequency band to process sensory stimuli.
German Acupuncture Trials (GERAC) for chronic low back pain: randomized, multicenter, blinded, parallel-group trial with 3 groups.

BACKGROUND To our knowledge, verum acupuncture has never been directly compared with sham acupuncture and guideline-based conventional therapy in patients with chronic low back pain. METHODS A patient- and observer-blinded randomized controlled trial conducted in Germany involving 340 outpatient practices, including 1162 patients aged 18 to 86 years (mean +/- SD age, 50 +/- 15 years) with a history of chronic low back pain for a mean of 8 years. Patients underwent ten 30-minute sessions, generally 2 sessions per week, of verum acupuncture (n = 387) according to principles of traditional Chinese medicine; sham acupuncture (n = 387) consisting of superficial needling at nonacupuncture points; or conventional therapy, a combination of drugs, physical therapy, and exercise (n = 388). Five additional sessions were offered to patients who had a partial response to treatment (10%-50% reduction in pain intensity). Primary outcome was response after 6 months, defined as 33% improvement or better on 3 pain-related items on the Von Korff Chronic Pain Grade Scale questionnaire or 12% improvement or better on the back-specific Hanover Functional Ability Questionnaire. Patients who were unblinded or had recourse to other than permitted concomitant therapies during follow-up were classified as nonresponders regardless of symptom improvement. RESULTS At 6 months, response rate was 47.6% in the verum acupuncture group, 44.2% in the sham acupuncture group, and 27.4% in the conventional therapy group. Differences among groups were as follows: verum vs sham, 3.4% (95% confidence interval, -3.7% to 10.3%; P = .39); verum vs conventional therapy, 20.2% (95% confidence interval, 13.4% to 26.7%; P < .001); and sham vs conventional therapy, 16.8% (95% confidence interval, 10.1% to 23.4%; P < . 001. CONCLUSIONS Low back pain improved after acupuncture treatment for at least 6 months. Effectiveness of acupuncture, either verum or sham, was almost twice that of conventional therapy.
Adaptive Online Learning Algorithms for Blind Separation: Maximum Entropy and Minimum Mutual Information

There are two major approaches for blind separation: maximum entropy (ME) and minimum mutual information (MMI). Both can be implemented by the stochastic gradient descent method for obtaining the demixing matrix. The MI is the contrast function for blind separation; the entropy is not. To justify the ME, the relation between ME and MMI is first elucidated by calculating the first derivative of the entropy and proving that the mean subtraction is necessary in applying the ME and at the solution points determined by the MI, the ME will not update the demixing matrix in the directions of increasing the cross-talking. Second, the natural gradient instead of the ordinary gradient is introduced to obtain efficient algorithms, because the parameter space is a Riemannian space consisting of matrices. The mutual information is calculated by applying the Gram-Charlier expansion to approximate probability density functions of the outputs. Finally, we propose an efficient learning algorithm that incorporates with an adaptive method of estimating the unknown cumulants. It is shown by computer simulation that the convergence of the stochastic descent algorithms is improved by using the natural gradient and the adaptively estimated cumulants.
Changes in protein expression in the rat medial vestibular nuclei during vestibular compensation

The molecular mechanisms of neural and synaptic plasticity in the vestibular nuclei during ‘vestibular compensation’, the behavioural recovery that follows deafferentation of one inner ear, are largely unknown. In this study we have used differential proteomics techniques to determine changes in protein expression in ipsi‐lesional and contra‐lesional medial vestibular nuclei (MVN) of rats, 1 week after either sham surgery or unilateral labyrinthectomy (UL). A systematic comparison of 634 protein spots in two‐dimensional electrophoresis gels across five experimental conditions revealed 54 spots, containing 26 proteins whose level was significantly altered 1 week post‐UL. The axon‐guidance‐associated proteins neuropilin‐2 and dehydropyriminidase‐related protein‐2 were upregulated in the MVN after UL. Changes in levels of further specific proteins indicate a coordinated upregulation of mitochondrial function, ATP biosynthesis and phosphate metabolism in the vestibular nuclei 1 week post‐UL. These may reflect the metabolic energy demands of processes such as gliosis, neuronal outgrowth and synaptic remodelling that occur after UL. Our findings suggest novel roles for axon elaboration and guidance molecules, as well as mitochondrial and metabolic regulatory proteins, in the post‐lesional physiology of the MVN during vestibular system plasticity.
d-Methadone blocks morphine tolerance and N-methyl-D-aspartate-induced hyperalgesia.

Previous in vitro and in vivo studies have determined that the d isomer of methadone has N-methyl-D-aspartate (NMDA) receptor antagonist activity. The present studies examined the ability of d-methadone to attenuate the development of morphine tolerance in mice and rats and to modify NMDA-induced hyperalgesia in rats. A decrease in the percentage of mice analgesic (tail-flick response) after 5 days of once-daily morphine (7 mg/kg s.c.) was completely blocked by coadministration of d-methadone given s.c. at 10 mg/kg. Morphine given s.c. to mice on an escalating three times per day dosing schedule resulted in a nearly 3-fold increase in the tail-flick ED50 dose of morphine which was prevented by s.c. coadministered d-methadone at 15 mg/kg. In rats, intrathecal (i.t.) morphine produced a 38-fold increase in the ED50, which was completely prevented by the coadministration of i.t. d-methadone at 160 micrograms/rat. A decrease in thermal paw withdrawal latency induced by the i.t. administration of 1.64 micrograms/rat NMDA was completely blocked by pretreatment with 160 micrograms/rat d-methadone. Thus, systemically coadministered d-methadone prevents systemically induced morphine tolerance in mice, i.t. d-methadone attenuates tolerance produced by i.t. morphine in rats, and i.t. d-methadone, at the same dose which modulates morphine tolerance, blocks NMDA-induced hyperalgesia. These results support the conclusion that d-methadone affects the development of morphine tolerance and NMDA-induced hyperalgesia by virtue of its NMDA receptor antagonist activity.