Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Motivational Interviewing on Craving and Dependence on Hookah in Suburban Pregnant Women in South East of Iran

Abstract Hookah smoking during pregnancy is a health concern which requires effective interventions. Thus, the authors have aimed to evaluate the effect of motivational interviewing on craving and dependence on hookah in pregnant women (n = 140) addicted to hookah who reside in the outskirts of Zahedan, a city in southeast of Iran. The subjects were selected using the convenience sampling and randomly divided into either the control or intervention group. The intervention group received five motivational interviewing group sessions about hookah smoking withdrawal, whereas the control group was given the conventional recommendations for quitting hookah. Data were collected after 8 weeks during the post intervention period using Hookah Craving Test and Hookah Addiction Severity Index. Next, they were analyzed using independent t-test, paired t-test, and analysis of covariance (ANCOVA). After the motivational interviewing intervention, the independent t-test indicated a significant difference between the intervention and control groups in terms of the mean score of hookah craving (P = 0.0001). Moreover, ANCOVA, with control of the effect of pretest and duration of hookah addiction, demonstrated a significant difference between the two groups regarding the mean score of hookah dependence after the intervention (P = 0.0001). Motivational interviewing had a significant positive impact on decreased hookah craving and dependence (two indices of withdrawal). Therefore, healthcare providers are recommended to incorporate motivational interviewing-based education into prenatal care programs to promote the chance of hookah smoking withdrawal.
The Effect of Ball Milling and Fatty Acid Addition on the Properties of MgB 2 Wires

Improved inductive critical current density, Jc, at medium and high magnetic fields, B, has been obtained in MgB2 wires made from ball milled and carbon doped precursors. The analyzed Fe-sheathed mono-filamentary wires have been manufactured by the powder-in-tube (PIT) and in-situ methods. C doping has been achieved by the addition of fatty acids, in particular oleic acid (C18H34O2). In order to enhance the Jc(B) performance and the homogeneity of the wires, we have analyzed the combined effects of ball milling and oleic acid addition. The changes in the microstructure, phase composition and superconducting properties for different milling parameters and fixed amount of acid addition have been analyzed.
Fate of 15N labeled nitrogen in maize grown with nutriseed pack using tracer technique

Deep placement of fertilizers will reduce the nutrient losses to the environment and increases the nutrient use efficiency. Nutriseed pack is a small tubular assembly consisting seed with bio-inoculants on top, manure pellet in middle and fertilizer pellet at bottom. A field study has been taken to determine nitrogen recovery and to evaluate the compatibility of phosphorus fertilizer sources with nitrogen sources which suited for Nutriseed pack by estimating the recovery of applied fertilizer N added as 15N labeled urea with Nutriseed pack in maize and retention in soil using 15N tracer technique in eastern block of Tamil Nadu Agricultural University, Coimbatore. This study has revealed that the actual nitrogen recovery from fertilizer and fertilizer nitrogen retention in the soil. The highest fertilizer nitrogen recovery (15N) in leaves, stem and grain (47.95 %) was found with NP(DAP)K Nutriseed pack with phosphorus as Di ammonium phosphate placement recording the highest nitrogen use efficiency of 64.91%. Relatively low recovery of nitrogen (45.25%) was observed with NP(SSP)K Nutriseed pack with phosphorus as Single super phosphate placement recording 58.67% of nitrogen use efficiency. The labeled nitrogen retention in soil is recorded low in NP(DAP)K Nutriseed pack placement and comparatively high in NP(SSP)K Nutriseed pack placement.
Belief-Space Planning for Automated Malware Defense

Malware detection and response is critical to ensuring information security across a wide range of devices. There have been few attempts, however, to develop security systems that exploit the benefits of different malware detection techniques. We formally introduce an automated malware defense framework and represent it as a belief-space planning problem that optimally reduces the impact on the performance of a system. Using the framework, we then provide an example automated malware defense system for email worm detection and response. Finally, we show in simulation that the system outperforms standard security techniques that have been used in practice. The result is a novel belief-space planning approach to automated malware defense designed for robust, accurate, and efficient use in large networks of resourceconstrained devices.
Mental health consumer participation in undergraduate occupational therapy student assessment: No negative impact

BACKGROUND/AIM Australian accreditation standards for occupational therapy courses require consumer participation in the design, delivery and evaluation of programs. This study investigated whether a mental health consumer - as one of two assessors for an oral assessment in a mental health unit - impacted engagement, anxiety states and academic performance of undergraduate occupational therapy students. METHODS Students (n = 131 eligible) self-selected into two groups but were blinded to the group differences (assessor panel composition) until shortly prior to the oral assessment. Control group assessors were two occupational therapy educators, while consumer group assessors included an occupational therapy educator and a mental health consumer. RESULTS Pre- and post-assessment data were successfully matched for 79 students (overall response rate = 73.1%). No evidence was found of significant differences between the two groups for engagement, anxiety or academic performance (all P values >0.05). CONCLUSION Including mental health consumers as assessors did not negatively impact student engagement and academic performance, nor increase student anxiety beyond that typically observed in oral assessment tasks. The findings provide support for expanding the role of mental health consumers in the education and assessment of occupational therapy students. Development of methods to determine the efficacy of consumer involvement remains an area for future research.
Cdk5 Inhibitory Peptide Prevents Loss of Dopaminergic Neurons and Alleviates Behavioral Changes in an MPTP Induced Parkinson’s Disease Mouse Model

Parkinson’s disease (PD) is one of the most affected neurodegenerative diseases in the world. Deregulation of cyclin-dependent kinase 5 (Cdk5) is believed to play an important role in neurodegenerative diseases including PD. p25 is a cleavage peptide of p35, a physiologic activator of Cdk5. p25 combines to Cdk5 and leads to the hyperactivity of Cdk5, which in turn hyperphosphorylates downstream substrates and leads to neuroinflammation and apoptosis of neurons. Previously, we have demonstrated that adeno-associated virus serotype-9 (AAV9) mediated Cdk5 inhibitory peptide (CIP) inhibits the activity of Cdk5/p25 complex and alleviates pathologic and behavioral changes in Alzheimer’s disease mouse model. In this study, we evaluated whether AAV9-CIP protected dopaminergic (DA) neurons in 1-methyl-4-phe-nyl-1,2,3,6-tetrahydropyridine-probenecid (MPTP/p) induced PD mouse model. The data showed that administration of AAV9-CIP by intracerebroventricular injection 1 week before MPTP/p exposure protected loss of DA neurons in substantia nigra compact of the model mice. Importantly, AAV9-CIP also alleviated the motor and anxiety-like symptoms of the disease animals. In summary, AAV9 mediated CIP might be a potential intervention for PD.
Progress in Gene Therapy to Prevent Retinal Ganglion Cell Loss in Glaucoma and Leber's Hereditary Optic Neuropathy

The eye is at the forefront of the application of gene therapy techniques to medicine. In the United States, a gene therapy treatment for Leber's congenital amaurosis, a rare inherited retinal disease, recently became the first gene therapy to be approved by the FDA for the treatment of disease caused by mutations in a specific gene. Phase III clinical trials of gene therapy for other single-gene defect diseases of the retina and optic nerve are also currently underway. However, for optic nerve diseases not caused by single-gene defects, gene therapy strategies are likely to focus on slowing or preventing neuronal death through the expression of neuroprotective agents. In addition to these strategies, there has also been recent interest in the potential use of precise genome editing techniques to treat ocular disease. This review focuses on recent developments in gene therapy techniques for the treatment of glaucoma and Leber's hereditary optic neuropathy (LHON). We discuss recent successes in clinical trials for the treatment of LHON using gene supplementation therapy, promising neuroprotective strategies that have been employed in animal models of glaucoma and the potential use of genome editing techniques in treating optic nerve disease.
Dynein–Dynactin–NuMA clusters generate cortical spindle-pulling forces as a multi-arm ensemble

To position the mitotic spindle within the cell, dynamic plus ends of astral microtubules are pulled by membrane-associated cortical force-generating machinery. However, in contrast to the chromosome-bound kinetochore structure, how the diffusion-prone cortical machinery is organized to generate large spindle-pulling forces remains poorly understood. Here, we develop a light-induced reconstitution system in human cells. We find that induced cortical targeting of NuMA, but not dynein, is sufficient for spindle pulling. This spindle-pulling activity requires dynein-dynactin recruitment by NuMA’s N-terminal long arm, dynein-based astral microtubule gliding, and NuMA’s direct microtubule-binding activities. Importantly, we demonstrate that cortical NuMA assembles specialized focal structures that cluster multiple force-generating modules to generate cooperative spindle-pulling forces. This clustering activity of NuMA is required for spindle positioning, but not for spindle-pole focusing. We propose that cortical Dynein-Dynactin-NuMA (DDN) clusters act as the core force-generating machinery that organizes a multi-arm ensemble reminiscent of the kinetochore.
A Review of Podocyte Biology

Background: Podocyte biology is a developing science that promises to help improve understanding of the mechanistic nature of multiple diseases associated with proteinuria. Proteinuria in nephrotic syndrome has been linked to mechanistic dysfunctions in the renal glomerulus involving the function of podocyte epithelial cells, including podocyte foot process effacement. Summary: Developments in imaging technology are improving knowledge of the detailed structure of the human renal glomerulus and cortex. Podocyte foot processes attach themselves to the glomerular capillaries at the glomerular basement membrane (GBM) forming intercellular junctions that form slit diaphragm filtration barriers that help maintain normal renal function. Damage in this area has been implicated in glomerular disease. Injured podocytes undergo effacement whereby they lose their structure and spread out, leading to a reduction in filtration barrier function. Effacement is typically associated with the presence of proteinuria in focal segmental glomerulosclerosis, minimal change disease, and diabetes. It is thought to be due to a breakdown in the actin cytoskeleton of the foot processes, complex contractile apparatuses that allow podocytes to dynamically reorganize according to changes in filtration requirements. The process of podocyte depletion correlates with the development of glomerular sclerosis and chronic kidney disease. Focal adhesion complexes that interact with the underlying GBM bind the podocytes within the glomerular structure and prevent their detachment. Key Messages: Knowledge of glomerular podocyte biology is helping to advance our understanding of the science and mechanics of the glomerular filtering process, opening the way to a variety of new potential applications for clinical targeting.
Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome

BACKGROUND The efficacy of venovenous extracorporeal membrane oxygenation (ECMO) in patients with severe acute respiratory distress syndrome (ARDS) remains controversial. METHODS In an international clinical trial, we randomly assigned patients with very severe ARDS, as indicated by one of three criteria — a ratio of partial pressure of arterial oxygen (Pao2) to the fraction of inspired oxygen (Fio2) of less than 50 mm Hg for more than 3 hours; a Pao2:Fio2 of less than 80 mm Hg for more than 6 hours; or an arterial blood pH of less than 7.25 with a partial pressure of arterial carbon dioxide of at least 60 mm Hg for more than 6 hours — to receive immediate venovenous ECMO (ECMO group) or continued conventional treatment (control group). Crossover to ECMO was possible for patients in the control group who had refractory hypoxemia. The primary end point was mortality at 60 days. RESULTS At 60 days, 44 of 124 patients (35%) in the ECMO group and 57 of 125 (46%) in the control group had died (relative risk, 0.76; 95% confidence interval [CI], 0.55 to 1.04; P=0.09). Crossover to ECMO occurred a mean (±SD) of 6.5±9.7 days after randomization in 35 patients (28%) in the control group, with 20 of these patients (57%) dying. The frequency of complications did not differ significantly between groups, except that there were more bleeding events leading to transfusion in the ECMO group than in the control group (in 46% vs. 28% of patients; absolute risk difference, 18 percentage points; 95% CI, 6 to 30) as well as more cases of severe thrombocytopenia (in 27% vs. 16%; absolute risk difference, 11 percentage points; 95% CI, 0 to 21) and fewer cases of ischemic stroke (in no patients vs. 5%; absolute risk difference, ‐5 percentage points; 95% CI, ‐10 to ‐2). CONCLUSIONS Among patients with very severe ARDS, 60‐day mortality was not significantly lower with ECMO than with a strategy of conventional mechanical ventilation that included ECMO as rescue therapy. (Funded by the Direction de la Recherche Clinique et du Développement and the French Ministry of Health; EOLIA ClinicalTrials.gov number, NCT01470703.)
Online Self-Administered Cognitive Testing Using the Amsterdam Cognition Scan: Establishing Psychometric Properties and Normative Data

Background Online tests enable efficient self-administered assessments and consequently facilitate large-scale data collection for many fields of research. The Amsterdam Cognition Scan is a new online neuropsychological test battery that measures a broad variety of cognitive functions. Objective The aims of this study were to evaluate the psychometric properties of the Amsterdam Cognition Scan and to establish regression-based normative data. Methods The Amsterdam Cognition Scan was self-administrated twice from home—with an interval of 6 weeks—by 248 healthy Dutch-speaking adults aged 18 to 81 years. Results Test-retest reliability was moderate to high and comparable with that of equivalent traditional tests (intraclass correlation coefficients: .45 to .80; .83 for the Amsterdam Cognition Scan total score). Multiple regression analyses indicated that (1) participants’ age negatively influenced all (12) cognitive measures, (2) gender was associated with performance on six measures, and (3) education level was positively associated with performance on four measures. In addition, we observed influences of tested computer skills and of self-reported amount of computer use on cognitive performance. Demographic characteristics that proved to influence Amsterdam Cognition Scan test performance were included in regression-based predictive formulas to establish demographically adjusted normative data. Conclusions Initial results from a healthy adult sample indicate that the Amsterdam Cognition Scan has high usability and can give reliable measures of various generic cognitive ability areas. For future use, the influence of computer skills and experience should be further studied, and for repeated measurements, computer configuration should be consistent. The reported normative data allow for initial interpretation of Amsterdam Cognition Scan performances.
Forward Amortized Inference for Likelihood-Free Variational Marginalization

In this paper, we introduce a new form of amortized variational inference by using the forward KL divergence in a joint-contrastive variational loss. The resulting forward amortized variational inference is a likelihood-free method as its gradient can be sampled without bias and without requiring any evaluation of either the model joint distribution or its derivatives. We prove that our new variational loss is optimized by the exact posterior marginals in the fully factorized mean-field approximation, a property that is not shared with the more conventional reverse KL inference. Furthermore, we show that forward amortized inference can be easily marginalized over large families of latent variables in order to obtain a marginalized variational posterior. We consider two examples of variational marginalization. In our first example we train a Bayesian forecaster for predicting a simplified chaotic model of atmospheric convection. In the second example we train an amortized variational approximation of a Bayesian optimal classifier by marginalizing over the model space. The result is a powerful meta-classification network that can solve arbitrary classification problems without further training.
ENZYME BASED METHODS FOR LACTATE DETERMINATION

Development of biosensors for lactate determination has gained an increased research interest because of their wide application in clinical analysis and control of fermentation processes in food industry. Lactate biosensors with enzyme modified modules are a perspective alternative to the conventional methods in clinical analysis for their fast response, applicability to continuous mode of analysis, low cost and easy automation. Food and beverage industry can also benefit of the advantages of lactate biosensors for monitoring of fermentation processes or control of foods labeled as “low lactate content”. The quantification of low lactate levels demands for sensitive and reliable analytical methods for lactate quantification in complex matrices. This review discusses the enzymatic methods for lactate determination. Recent advances in lactate biosensors development are summarized. Analytical bioreactors and biosensors for application in flow injection analysis are specially emphasized.
Conformation Clustering of Long MD Protein Dynamics with an Adversarial Autoencoder

Recent developments in specialized computer hardware have greatly accelerated atomic level Molecular Dynamics (MD) simulations. A single GPU-attached cluster is capable of producing microsecond-length trajectories in reasonable amounts of time. Multiple protein states and a large number of microstates associated with folding and with the function of the protein can be observed as conformations sampled in the trajectories. Clustering those conformations, however, is needed for identifying protein states, evaluating transition rates and understanding protein behavior. In this paper, we propose a novel data-driven generative conformation clustering method based on the adversarial autoencoder (AAE) and provide the associated software implementation Cong. The method was tested using a 208 microseconds MD simulation of the fast-folding peptide Trp-Cage (20 residues) obtained from the D.E. Shaw Research Group. The proposed clustering algorithm identifies many of the salient features of the folding process by grouping a large number of conformations that share common features not easily identifiable in the trajectory.
Semantic Road Layout Understanding by Generative Adversarial

Autonomous driving is becoming a reality, yet vehicles still need to rely on complex sensor fusion techniques to fully understand the scene they act in. Being able to discern the static environment from the dynamic entities that populate it, will improve scene comprehension algorithms and will pose constraints to the reasoning process about moving objects. With this in mind, we propose a scene comprehension task aimed at providing a complete understanding of the static surroundings, with a particular attention to road layout. In order to cut to the bare minimum the sensor requirements to be deployed on-board, we solely rely on semantic segmentation masks, which can be reliably obtained with computer vision algorithms from any RGB source. We cast this problem as an inpainting task based on a Generative Adversarial Network model to remove all dynamic objects from the scene and focus on understanding its static components such as streets, sidewalks and buildings. We evaluate this task on a synthetically generated dataset obtained with the CARLA simulator, demonstrating the effectiveness of our method.
The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain

Antimicrobial resistance (AMR) surveillance is a critical step within risk assessment schemes, as it is the basis for informing global strategies, monitoring the effectiveness of public health interventions, and detecting new trends and emerging threats linked to food. Surveillance of AMR is currently based on the isolation of indicator microorganisms and the phenotypic characterization of clinical, environmental and food strains isolated. However, this approach provides very limited information on the mechanisms driving AMR or on the presence or spread of AMR genes throughout the food chain. Whole-genome sequencing (WGS) of bacterial pathogens has shown potential for epidemiological surveillance, outbreak detection, and infection control. In addition, whole metagenome sequencing (WMS) allows for the culture-independent analysis of complex microbial communities, providing useful information on AMR genes occurrence. Both technologies can assist the tracking of AMR genes and mobile genetic elements, providing the necessary information for the implementation of quantitative risk assessments and allowing for the identification of hotspots and routes of transmission of AMR across the food chain. This review article summarizes the information currently available on the use of WGS and WMS for surveillance of AMR in foodborne pathogenic bacteria and food-related samples and discusses future needs that will have to be considered for the routine implementation of these next-generation sequencing methodologies with this aim. In particular, methodological constraints that impede the use at a global scale of these high-throughput sequencing (HTS) technologies are identified, and the standardization of methods and protocols is suggested as a measure to upgrade HTS-based AMR surveillance schemes.