Miracle-dz/UniFAR-FTUs huggingface dataset:
Distress Syndrome Procollagen Levels in Acute Respiratory Lavage Fluid Angiogenic Activity and Bronchoalveolar Chemokines Correlates with Imbalance in the Expression of CXC

Diffuse alveolar damage is the histopathological hallmark of acute respiratory distress syndrome (ARDS) and is a stereotypic response to a variety of etiologies. Moreover, a signiﬁcant proportion of ARDS survivors have residual pulmonary ﬁbrosis and compromised pulmonary function. This suggests that the pathogenesis of diffuse alveolar damage that ultimately leads to the chronic ﬁbrosis of ARDS has features of dysregulated repair exempliﬁed by exaggerated intra-alveolar angiogenesis and ﬁbrogenesis (i.e., ﬁbroproliferation and deposition of extracellular matrix), leading to progressive alveolar ﬁbrosis and impaired lung function. We obtained bronchoalveolar lavage ﬂuid (BALF) from patients with ARDS or ventilated control patients and assessed CXC chemokine levels by ELISA. We found an imbalance in the expression of ELR (cid:1) as compared with ELR (cid:2) CXC chemokines from BALF of patients with ARDS as compared with controls. This imbalance correlated with angiogenic activity as assessed by the corneal micropocket assay. Furthermore, these levels correlated with both procollagen I and procollagen III levels in BALF. In contrast, while BALF levels of vascular endothelial growth factor were elevated, vascular endothelial growth factor did not appear to be signiﬁcantly contributing to the angiogenic activity. These ﬁndings suggest that CXC chemokines have an important role in the ﬁbroproliferative phase of ARDS via the regulation of angiogenesis. The Journal of Immunology, 2002, 169: 6515–6521.
Rare-earth metal complexes derived from the acids Ph ​ 2 ​ C(X)CO ​ 2 ​ H (X= OH, NH ​ 2 ​ ): Structural

of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, P. R. China. *C.Redshaw@hull.ac. uk Abstract: ​ Treatment of Ln(NO ​ 3 ​ ) ​ 3 ​ . ​ 6H ​ 2 ​ O (Ln = La, Ce) with an equimolar amount of 2,2’-diphenylglycine (DpgH) in ethanol afforded the corresponding hexacoordinated complexes (DpgH ​ ± ​ ) ​ 3 ​ Ln(NO ​ 3 ​ ) ​ 3 ​ . ​ H ​ 2 ​ O (DpgH ​ ± = zwitterionic 2,2’-diphenylglycine, Ln = La ( ​ 1 ​ ), Ce ( ​ 2 ​ )). The spectroscopic and structural features of these compounds have been investigated. Similar reactions with the related benzilic acid (BenzH ​ 2 ​ ) were unsuccessful. The catalytic behaviour of ​ 1 and ​ 2 in the homo- and copolymerization of ​ ε ​ -caprolactone ( ​ ε ​ -CL) and rac ​ -lactide ( ​ r ​ -LA) has been investigated herein. In the case of ​ ε ​ -CL, the two complexes exhibited comparable activity, allowing for complete monomer conversion under aerobic and solvent-free conditions at also examined. Interestingly, only BenzH ​ 2 was found to be active, although it required a higher catalyst loading and the presence of benzyl alcohol as
Mobile Learning Experiences in the Philippine Education Setting Using Portable Moodle

— In an attempt to achieve innovative teaching and learning in provinces where an Internet connection is a challenge, a USB-based portable learning management system was developed. This paper is aimed at describing the experiences in implementing a USB-based learning management system in teacher education in the Philippines. Specifically, this article presents Silliman University’s experiences in customizing a tool for innovative teaching and learning in teacher education. It describes the result of the pilot implementation of the tool among the select higher education institutions in Central Visayas, Philippines. This paper also presents the reflection and lessons learned by the teacher educators and students in the learning management system. The learning management system was customized using POODLE, a portable MOODLE. It can run on a USB flash drive without an internet connection. A total of 16 trained teacher educators in Central Visayas, Philippines were selected as pilot-teachers. The study reveals that the implementation varies among the pilot-teachers in terms of level, mode, and terminal usage which are all affected by many variables. It was discovered that there are more facilitating factors than hindering factors in implementing POODLE for mobile learning. The study found out that POODLE is a useful tool for mobile learning in areas where internet connection is limited.
Transcutaneous Electrical Nerve Stimulation Parameters in Spasticity

frequency was effective in spasticity reduction [9], there is still a lack of randomized clinical trials regarding with the other parameters of TENS. Across the various studies, the pulse duration was applied in a range from 0.1 to 0.3 milliseconds, resulting in spasticity reduction. It is very intriguing which pulse duration parameter would be optimal for spasticity improvement. The same speculation is applicable to the stimulating intensity, duration of treatment session and total duration of clinical trial.
Metabolic adaptation revealed: a transcriptome comparison of lkb1 and wt larvae during yolk depletion and prolonged fasting

Metabolic adaptation is important for the survival of an organism during times of varying nutrient availability or after disruption of the maternal nutrient supply. During the development of zebrafish larvae, metabolic adaptation occurs during yolk depletion. We have previously shown that zebrafish larvae mutated in lkb1 fail to adapt their metabolism shortly after yolk depletion. To investigate the role of Lkb1 in the process of metabolic adaptation, we compared the transcriptomes of wild-type and lkb1 larvae, before and after yolk depletion, and during prolonged fasting. We show that the expression profile of lkb1 larvae after yolk depletion overlaps with that of wild-type larvae during prolonged fasting, thereby confirming a premature starvation state of lkb1 larvae. Furthermore, we find that lkb1 larvae show upregulation of lepb, il6 and il1b , genes associated with cachexia pathophysiology. Finally, we find a gene set whose expression appears to be regulated directly by Lkb1 and independent of the presence of yolk, including unexpectedly, deregulation of the expression of several β - and γ -crystallin genes. the of
Edinburgh Research Explorer Essential and distinct roles for cdc42 and rac1 in the regulation of Schwann cell biology during peripheral nervous system development

uring peripheral nervous system (PNS) myelination, Schwann cells must interpret extracellular cues to sense their environment and regulate their intrinsic developmental program accordingly. The pathways and mechanisms involved in this process are only par-tially understood. We use tissue-speciﬁ c conditional gene targeting to show that members of the Rho GTPases, cdc42 and rac1, have different and essential roles in axon sorting by Schwann cells. Our results indicate that although cdc42 is required for normal Schwann cell proliferation, rac1 regulates Schwann cell process extension and stabilization, allowing efﬁ cient radial sorting of axon bundles.
Efficacy of Involuntary Deep Breathing by Postural-Respiration Feedback Control System

— This study was undertaken to quantify heart rate dynamics and interactions during sequential use of a postural-respiration feedback regulation control system. The bent shape of the human back makes it easier to exhale air from the lungs, but challenging to inhale. On the other hand, when a human being leans over backwards, it becomes difficult to exhale, but easier to inhale. This simple feature opens up the possibility of regulating human breathing involuntarily through posture control. We developed and tested a postural-respiration feedback regulation control system. The process of the posture control architecture depends on an air chamber placed under the subject’s back. For this experiment, subjects had to lie on a bed, and the subjects’ respiration cycle was synchronized with the inflation and deflation of the air chamber. We analyzed the beat-to-beat heart rate and the continuous breathing signal data gathered from ten male university students. We investigated the hypothesis that the use of a synchronously controlled postural-respiration feedback control system would yield positive psychophysiological benefits. The heart rate and respiratory dynamics from the deep breathing response and segmented breathing were similar. The results indicate that deep breathing was successfully induced when posture control was precisely synchronized with the subject’s own respiration. The implications of these findings for both future research and practice are addressed in a comprehensive discussion.
Moghaddam, Nima Golijani and Coxon, Helen and Nabarro, Sally and Cox, Karen (2016) Unmet care needs in people living with advanced cancer: a systematic review. Supportive Care

Purpose The support needs of cancer patients vary according to the phase of their cancer journey. Recent developments in healthcare are such that the advanced cancer phase is increasingly experienced as a chronic illness phase, with consequent changes in patient support needs. Understanding these needs, and identifying areas of unmet need, can enable us to develop services that are more adequate to the task of supporting this population. Methods We conducted a systematic search of four electronic databases to identify studies examining the unmet needs of people living with advanced cancer. Relevant data were extracted and synthesised; meta-analyses were conducted to obtain pooled estimates for prevalence of needs. Results We identified 23 studies (4 qualitative) for inclusion. Unmet needs were identified across a broad range of domains, with greatest prevalence in informational (30-55%), psychological (18-42%), physical (17-48%), and functional (17-37%) domains. There was considerable heterogeneity amongst studies in terms of methods of assessment, coding and reporting of needs, respondent characteristics, and appraised study quality Conclusions Heterogeneity made it difficult to compare across studies and inflated confidence intervals for pooled estimates of prevalence – we need standardised and comprehensive approaches to assessment and reporting of unmet needs to further our understanding. Nonetheless, the review identified prominent needs across a range of (interacting) experiential domains. Moreover, by focussing on unmet needs for support, we were able to extrapolate potential implications for service development.
Gene proﬁling of polycystic kidneys

Background. While the genetic basis of autosomal dominant polycystic kidney disease (ADPKD) has been clearly established, the pathogenesis of renal failure in ADPKD remains elusive. Cyst formation originates from proliferating renal tubular epithelial cells that de-differentiate. Fluid secretion with cyst expansion and reactive changes in the extracellular matrix composition combined with increased apoptosis and proliferation rates have been implicated in cystogenesis. Methods. To identify genes that characterize pathogenical changes in ADPKD, we compared the expression proﬁles of 12 ADPKD kidneys, 13 kidneys with chronic transplant nephropathy and 16 normal kidneys using a 7 k cDNA microarray. RT–PCR and immunohistochemical techniques were used to conﬁrm the microarray data. Results. Hierarchical clustering revealed that the gene expression proﬁles of normal, ADPKD and rejected kidneys were clearly distinct. A total of 87 genes were speciﬁcally regulated in ADPKD; 26 of these 87 genes were typical for smooth muscle, suggesting epithelial-to-myoﬁbroblast transition (EMT) as a pathogenetic factor in ADPKD. Immunohistology revealed that smooth muscle actin, a typical marker for myoﬁbroblast transition, and caldesmon were mainly expressed in the interstitium of ADPKD kidneys. In contrast, up-regulated keratin 19 and ﬁbulin-1 were conﬁned to cystic epithelia. Conclusion. Our results show that the end stage of ADPKD is associated with increased markers of EMT, suggesting that EMT contributes to the progressive loss of renal function in ADPKD.
Suppliers of Existing Systems in Municipal Healthcare Facing the Arrival of Large-Scale EHR Suites

With backing from national health authorities, large-scale electronic health record (EHR) suites have increasingly entered the European healthcare market. The overall goal for these systems is to fulfill the needs of healthcare workers in hospitals, nursing homes, home-care service, and general practitioner (GP) clinics. The EHR suites will replace existing EHRs in their targeted area. However, the national and regional authorities cannot mandate that municipalities and GPs implement these new EHR systems. Therefore, there will still be ways for the suppliers of existing systems to compete for market share and provide municipalities and GPs with viable alternatives. We explore these issues by focusing on how suppliers of the EHRs currently used by municipalities maneuver under the imminent threat from an EHR suite. Empirically, we focus on the three principal suppliers of EHR systems to the Norwegian municipal healthcare market. They are facing the introduction of a large-scale EHR suite in Central Norway in 2022 combined with the long-term national ambition of a common EHR system for the rest of the municipal health sector in Norway. Conceptually, we draw on information infrastructure literature.
Malliavin-Stein method for variance-gamma approximation on Wiener space

We combine Malliavin calculus with Stein's method to derive bounds for the Variance-Gamma approximation of functionals of isonormal Gaussian processes, in particular of random variables living inside a fixed Wiener chaos induced by such a process. The bounds are presented in terms of Malliavin operators and norms of contractions. We show that a sequence of distributions of random variables in the second Wiener chaos converges to a Variance-Gamma distribution if and only if their moments of order two to six converge to that of a Variance-Gamma distributed random variable (six moment theorem). Moreover, simplified versions for Laplace or symmetrized Gamma distributions are presented. Also multivariate extensions and a universality result for homogeneous sums are considered.
GENETIC ANALYSIS OF PENDULOUS CROP IN TURKEY Accuracy of genomic selection for reducing susceptibility to pendulous crop in turkey (Meleagris gallopavo)

Pendulous crop (PC) in the turkey occurs when the crop distends from its normal position, thereby preventing the movement of feed and water from the crop down into the digestive system. This condition negatively impacts the turkey industry at both production and welfare levels. In this study, we estimated the genetic parameters for PC incidence and its genetic correlation with five production traits. Additionally, we evaluated the prediction accuracy and bias of breeding values for the selection candidates using pedigree (BLUP) or pedigree-genomic (ssGBLUP) relationships among the animals. A total of 245,783 turkey records were made available by Hybrid Turkeys, Kitchener, Canada. Of these, 6,545 were affected with PC. In addition, the data included 9,634 records for breast meat yield (BMY); 5,592 records for feed conversion ratio (FCR) and residual feed intake (RFI) in males; 170,844 records for body weight (BW) and walking score (WS) between 18 and 20 weeks of age for males (71,012) and females (99,832), respectively. Among this population, 36,830 were genotyped using a 65K SNP Illumina Inc. chip. While all animals passed the quality control criteria, only 53,455 SNP markers were retained for subsequent analysis. Heritability for PC was estimated at 0.16 ± 0.00 and 0.17 ± 0.00 using BLUP and ssGBLUP, respectively. The incidence of PC was not genetically correlated with WS or FCR. Low unfavourable genetic correlations with BW (0.12 and 0.14), BMY (0.24 and 0.24) and RFI (-0.33 and -0.28) were obtained using BLUP and ssGBLUP, respectively. Using ssGBLUP showed higher prediction accuracy (0.51) for the breeding values for the selection candidates than the pedigree-based model (0.35). Whereas the bias of the prediction was slightly reduced with ssGBLUP (0.33 ± 0.05) than BLUP
Linear colliders based on laser-plasma accelerators

Laser-plasma accelerators are capable of sustaining accelerating fields of 10–100 GeV/m, 100–1000 times that of conventional technology and the highest fields produced by any of the widely researched advanced accelerator concepts. Laser-plasma accelerators also intrinsically accelerate short particle bunches, several orders of magnitude shorter than that of conventional technology, which leads to reductions in beamstrahlung and, hence, savings in the overall power consumption to reach a desired luminosity. These properties make laser-plasma accelerators a promising accelerator technology for a more compact, less expensive high-energy linear collider providing multi-TeV polarized leptons. In this submission to the Snowmass 2021 Accelerator Frontier, we discuss the motivation for a laser-plasma-accelerator-based linear collider, the status of the field, and potential linear collider concepts up to 15 TeV. We outline the research and development path toward a collider based on laser-plasma accelerator technology, and highlight near-term and mid-term applications of this technology on the collider development path. The required experimental facilities to carry out this research are described. We conclude with community recommendations developed during Snowmass.
Asymptotic analysis of parameter estimation for the Ewens--Pitman partition

We derive the exact asymptotic distribution of the maximum likelihood estimator $(\hat{\alpha}_n, \hat{\theta}_n)$ of $(\alpha, \theta)$ for the Ewens--Pitman partition in the regime of $0<\alpha<1$ and $\theta>-\alpha$: we show that $\hat{\alpha}_n$ is $n^{\alpha/2}$-consistent and converges to a variance mixture of normal distributions, i.e., $\hat{\alpha}_n$ is asymptotically mixed normal, while $\hat{\theta}_n$ is not consistent and converges to a transformation of the generalized Mittag-Leffler distribution. As an application, we derive a confidence interval of $\alpha$ and propose a hypothesis testing of sparsity for network data. In our proof, we define an empirical measure induced by the Ewens--Pitman partition and prove a suitable convergence of the measure in some test functions, aiming to derive asymptotic behavior of the log likelihood.
Ground-state bistability of cold atoms in a cavity

We experimentally demonstrate an optical bistability between two hyperfine atomic ground states, using a single mode of an optical resonator in the collective strong coupling regime. Whereas in the familiar case, the bistable region is created through atomic saturation, we report an effect between states of high quantum purity, which is essential for future information storage. The nonlinearity of the transitions arise from cavity-assisted pumping between ground states of cold, trapped atoms and the stability depends on the intensity of two driving lasers. We interpret the phenomenon in terms of the recent paradigm of first-order, driven-dissipative phase transitions, where the transmitted and driving fields are understood as the order and control parameters, respectively. The saturation-induced bistability is recovered for infinite drive in one of the controls. The order of the transition is confirmed experimentally by hysteresis in the order parameter when either of the two control parameters is swept repeatedly across the bistability region and the underlying phase diagram is predicted in line with semiclassical mean-field theory.
Multi-scored sleep databases: how to exploit the multiple-labels in automated sleep scoring

Abstract Study Objectives Inter-scorer variability in scoring polysomnograms is a well-known problem. Most of the existing automated sleep scoring systems are trained using labels annotated by a single-scorer, whose subjective evaluation is transferred to the model. When annotations from two or more scorers are available, the scoring models are usually trained on the scorer consensus. The averaged scorer’s subjectivity is transferred into the model, losing information about the internal variability among different scorers. In this study, we aim to insert the multiple-knowledge of the different physicians into the training procedure. The goal is to optimize a model training, exploiting the full information that can be extracted from the consensus of a group of scorers. Methods We train two lightweight deep learning-based models on three different multi-scored databases. We exploit the label smoothing technique together with a soft-consensus (LSSC) distribution to insert the multiple-knowledge in the training procedure of the model. We introduce the averaged cosine similarity metric (ACS) to quantify the similarity between the hypnodensity-graph generated by the models with-LSSC and the hypnodensity-graph generated by the scorer consensus. Results The performance of the models improves on all the databases when we train the models with our LSSC. We found an increase in ACS (up to 6.4%) between the hypnodensity-graph generated by the models trained with-LSSC and the hypnodensity-graph generated by the consensus. Conclusion Our approach definitely enables a model to better adapt to the consensus of the group of scorers. Future work will focus on further investigations on different scoring architectures and hopefully large-scale-heterogeneous multi-scored datasets.
Robot Vitals and Robot Health: Towards Systematically Quantifying Runtime Performance Degradation in Robots Under Adverse Conditions

This letter addresses the problem of automatically detecting and quantifying performance degradation in remote mobile robots, in real-time, during task execution. A robot may encounter a variety of uncertainties and adversities during task execution, which can impair its ability to carry out tasks effectively and cause its performance to degrade. Such situations can be mitigated or averted by timely detection and intervention, e.g., by a remote human supervisor taking over control in teleoperation mode. Inspired by patient triaging systems in hospitals, we introduce the framework of “robot vitals” for estimating overall “robot health”. A robot's vitals are a set of lower-level metrics that estimate a variety of indicators of performance degradation faced by a robot at any given point in time. Robot health is a higher-level metric that combines robot vitals into a single scalar value estimate of performance degradation. Experiments, both in simulation and on a real mobile robot, demonstrate that the proposed robot vitals and robot health can be used effectively for online estimation of robot performance degradation during run-time.
Probability density estimation for sets of large graphs with respect to spectral information using stochastic block models

For graph-valued data sampled iid from a distribution µ , the sample moments are computed with respect to a choice of metric. In this work, we equip the set of graphs with the pseudo-metric deﬁned by the (cid:96) 2 norm between the eigenvalues of the respective adjacency matrices. We use this pseudo metric and the respective sample moments of a graph valued data set to infer the parameters of a distribution ˆ µ and interpret this distribution as an approximation of µ . We verify experimentally that complex distributions µ can be approximated well taking this approach.