Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of a Palliative Care Intervention in Moderating the Relationship Between Depression and Survival Among Individuals With Advanced Cancer

Objective: Randomized controlled trials (RCTs) of early palliative care interventions in advanced cancer have positively impacted patient survival, yet the mechanisms remain unknown. This secondary analysis of 2 RCTs assessed whether an early palliative care intervention moderates the relationship between depressive symptoms and survival. Method: The relationships among mood, survival, and early palliative care intervention were studied among 529 advanced cancer patients who participated in 2 RCTs. The first (N = 322) compared intervention versus usual care. The second (N = 207) compared early versus delayed intervention (12 weeks after enrollment). The interventions included an in-person consultation, weekly nurse coach-facilitated phone sessions, and monthly follow-up. Mood was measured using the Center for Epidemiologic Studies-Depression (CES-D) scale. Cox proportional hazard analyses were used to examine the effects of baseline CES-D scores, the intervention, and their interaction on mortality risk while controlling for demographic variables, cancer site, and illness severity. Results: The combined sample was 56% male (M = 64.7 years). Higher baseline CES-D scores were significantly associated with greater mortality risk (hazard ratio [HR] = 1.042, 95% confidence interval [CI] [1.017, 1.067], p = .001). However, participants with higher CES-D scores who received the intervention had a lower mortality risk (HR = .963, CI [0.933, 0.993], p = .018) even when controlling for demographics, cancer site, and illness-related variables. Conclusion: This study is the first to demonstrate that patients with advanced cancer who also have depressive symptoms benefit the most from early palliative care. Future research should be devoted to exploring the mechanisms responsible for these relationships.
Single Image Dehazing Using Color Attenuation Prior

removal from a single input hazy image. By creating a linear model for modelling the scene depth of the hazy image under this novel prior and learning the parameters of the model with a supervised learning method, the depth information can be well recovered. With the depth map of the hazy image, we can easily remove haze from a single image. Figure 1 shows an overview of the proposed dehazing method. To describe the formation of a hazy image, the atmospheric scattering model is widely used and it can be expressed as follows: () () () () e (1 e) d x d x x x        I J A (1) where I is the hazy image, J is the scene radiance representing the haze-free image, A is the atmospheric light,  is the scattering coefficient of the atmosphere and d is the depth of scene. By doing a lot of experiments on the hazy images, we find the statistics that the density of the haze is positively correlated with the difference between the brightness and the saturation in a single hazy image. Since the haze density increases along with the change of scene depth in general, we can make an assumption that the depth of the scene is positively correlated with the density of the haze and we have: () () () () d x c x v x s x    (2) As the difference between the brightness and the saturation can approximately represent the density of the haze, we boldly assume that the relationship among the scene depth d, the brightness v and the saturation s is linear. Based on this assumption, we can create a linear model as follows: 0 1 2 () () () d x v x s x       (3) where d is the scene depth, v is the brightness, s is the saturation, and (0  , 1  , 2 ) are the unknown linear coefficients. In order to determine the coefficients (0  , 1  , 2 ) accurately, a simple and efficient supervised learning method is used. The training data are necessary in the supervised learning method. A training sample consists of a hazy image and its corresponding ground truth depth map in our case. In order to obtain the accurate depth information as far …
A scheduler for mobile cloud based on weighted metrics and dynamic context evaluation

Resource scarcity is a major obstacle for many mobile applications, since devices have limited energy power and processing potential. As an example, there are applications that seamlessly augment human cognition and typically require resources that far outstrip mobile hardware's capabilities, such as language translation, speech recognition, and face recognition. The use of cloud computing may tackle this problem. This study presents SmartRank, a scheduling framework to perform load partitioning and offloading for mobile applications using cloud computing to increase performance in terms of response time. We first explore a benchmarking of face recognition application using mobile cloud and confirms its suitability to be used as case study with SmartRank. We have applied the approach to a face recognition process based on two strategies: cloudlet federation and resource ranking through balanced metrics (level of CPU utilization and round-trip time). Second, using a full factorial experimental design we tuned the SmartRank with the most suitable partitioning decision calibrating scheduling parameters. Nevertheless, SmartRank uses an equation that is extensible to include new parameters and make it applicable to other scenarios.
Persistent Herpesvirus Infections and Telomere Attrition Over 3 Years in the Whitehall II Cohort

The determinants of telomere attrition, a potential marker of cellular aging, are not well understood. Persistent herpesvirus infections including cytomegalovirus (CMV) infection may be particularly important for telomere dynamics via mechanisms such as inflammation, oxidative stress, and their impact on peripheral blood lymphocyte composition. This study examined the association of 4 human herpesviruses (CMV, herpes simplex virus type 1, human herpesvirus type 6, and Epstein-Barr virus) with change in leukocyte telomere length (LTL) over 3 years in 400 healthy individuals (aged 53-76 years) from the Whitehall II cohort. CMV, herpes simplex virus type 1, and human herpesvirus 6 infection were independently associated with greater 3-year LTL attrition, with no association found for Epstein-Barr virus. The magnitudes of these associations were large, for example, the equivalent of almost 12 years of chronological age for those CMV seropositive. Seropositivity to more herpesviruses was additively associated with greater LTL attrition (3 herpesviruses vs none, β = -0.07 and P = .02; 4 infections vs none, β = -0.14 and P < .001). Higher immunoglobulin G antibody levels among those seropositive to CMV were also associated with shorter LTL at follow-up. These associations were robust to adjustment for age, sex, employment grade, body mass index, and smoking status. These results suggest that exposure to infectious agents should be an important consideration in future studies of telomere dynamics.
Deficit irrigation improves phenolic content and antioxidant activity in leafy lettuce varieties

Abstract This study investigated the effect of deficit irrigation at three management allowable depletion levels (MAD) 25%, 50%, and 75% on phytochemicals, ascorbic acid, antioxidant activity, glucose, fructose, and fresh and dry mass in two green leafy lettuce cultivars (Lollo Bionda and Vera) at harvest. Genotype response was observed during deficit irrigation on fresh and dry mass at harvest. Vera revealed similar fresh mass at MAD levels 25% and 50%. Chicoric acid, caftaric acid, and chlorogenic and caffeic acid tended to increase at 50% MAD, while kaempferol, quercetin, and myricetin increased at 75% MAD in both cultivars indicating increasing antioxidant properties. Ascorbic acid content declined with increasing MAD levels and no definite trend on β‐carotene content was noted in these cultivars with respect to MAD irrigation. Deficit irrigation at 50% and 70% increased glucose concentration in cv. Lollo Bionda. Deficit irrigation influences the abiotic stress condition that stimulates the biosynthesis of phytochemicals in plants and improves crop quality. However, deficit irrigation can affect marketable crop yield. Based on findings of this study, the lettuce cv. Vera can be recommended as a suitable cultivar for deficit irrigation (at MAD 50% levels) for improving dietary phytochemicals and crop quality without compromising fresh mass for marketing.
Genetic Architecture of a Rice Nested Association Mapping Population

Describing the genetic diversity in the gene pool of crops will provide breeders with novel resources for varietal improvement. Nested Association Mapping (NAM) populations are uniquely suited for characterizing parental diversity through the shuffling and fixation of parental haplotypes. Here, we describe a set of 1879 rice NAM lines created through the selfing and single-seed descent of F1 hybrids derived from elite IR64 indica crossed with 10 diverse tropical japonica lines. Genotyping data indicated tropical japonica alleles were captured at every queried locus despite the presence of segregation distortion factors. Several distortion loci were mapped, both shared and unique, among the 10 populations. Using two-point and multi-point genetic map calculations, our datasets achieved the ∼1500 cM expected map size in rice. Finally, we highlighted the utility of the NAM lines for QTL mapping, including joint analysis across the 10 populations, by confirming known QTL locations for the trait days to heading.
The Association Between Parental Mean Length of Utterance and Language Outcomes in Children With Disabilities: A Correlational Meta-Analysis.

PURPOSE The purpose of this correlational meta-analysis was to examine the association between parental utterance length and language outcomes in children with disabilities and whether this association varies according to other child characteristics, such as age and disability type. This association can serve as a starting point for language intervention practices for children with disabilities. METHOD We conducted a systematic search of 42 electronic databases to identify relevant studies. Twelve studies reporting on a total of 13 populations (including 257 participants) were identified. A random-effects model was used to estimate a combined effect size across all studies as well as separate effect sizes across studies in each disability category. RESULTS The combined effect size across all studies suggests a weak positive association between parental input length and child language outcomes. However, subgroup analyses within disability categories suggest that this association may differ for children with autism. Results of 4 studies including 47 children with autism show that parental input length is strongly associated with positive language outcomes in this population. CONCLUSIONS Present evidence suggests that clinicians should reconsider intervention practices that prescribe shorter, grammatically incomplete utterances, particularly when working with children with autism.
Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-identification

Most existing person re-identification (re-id) methods require supervised model learning from a separate large set of pairwise labelled training data for every single camera pair. This significantly limits their scalability and usability in real-world large scale deployments with the need for performing re-id across many camera views. To address this scalability problem, we develop a novel deep learning method for transferring the labelled information of an existing dataset to a new unseen (unlabelled) target domain for person re-id without any supervised learning in the target domain. Specifically, we introduce an Transferable Joint Attribute-Identity Deep Learning (TJ-AIDL) for simultaneously learning an attribute-semantic and identity-discriminative feature representation space transferrable to any new (unseen) target domain for re-id tasks without the need for collecting new labelled training data from the target domain (i.e. unsupervised learning in the target domain). Extensive comparative evaluations validate the superiority of this new TJ-AIDL model for unsupervised person re-id over a wide range of state-of-the-art methods on four challenging benchmarks including VIPeR, PRID, Market-1501, and DukeMTMC-ReID.
Impact of Sarcopenia on One-Year Mortality Among Older Hospitalized Patients with Impaired Mobility

ObjectivesHowever, the information regarding the impact of sarcopenia on mortality in older individuals is rising, there is a lack of knowledge concerning this issue among geriatric hospitalized patients. Therefore, aim of the present study was to investigate the associations between sarcopenia and 1-year mortality in a prospectively recruited sample of geriatric inpatients with different mobility and dependency status.Design and settingSarcopenia was diagnosed using the criteria of the European Working Group on Sarcopenia in Older People (EWGSOP). Hand grip strength and skeletal muscle mass were measured using Jamar dynamometer and bioelectrical impedance analysis, respectively. Physical function was assessed with the Short Physical Performance Battery. Dependency status was defined by Barthel-Index (BI). Mobility limitation was defined according to walking ability as described in BI. The survival status was ascertained by telephone interview.ResultsThe recruited population comprised 198 patients from a geriatric acute ward with a mean age of 82.8 ± 5.9 (70.2% females). 50 (25.3%) patients had sarcopenia, while 148 (74.7%) had no sarcopenia. 14 (28%) patients died among sarcopenic subjects compared with 28 (19%) non-sarcopenic subjects (P=0.229). After adjustment for potential confounders, sarcopenia was associated with increased mortality among patients with limited mobility prior to admission (n=138, hazard ratio, HR: 2.52, 95% CI: 1.17-5.44) and at time of discharge (n=162, HR: 1.93, 95% CI: 0.67-3.22). In a sub-group of patients with pre-admission BI<60 (n=45), <70 (n=73) and <80 (n=108), the risk of death was 3.63, 2.80 and 2.55 times higher in sarcopenic patients, respectively. In contrast, no significant relationships were observed between sarcopenia and mortality across the different scores of BI during admission and at time of discharge.ConclusionSarcopenia is significantly associated with higher risk of mortality among sub-groups of older patients with limited mobility and impaired functional status, independently of age and other clinical variables.
An image augmentation method using convolutional network for thyroid nodule classification by transfer learning

Thyroid nodules are severely jeopardizing our health. In the diagnosis of thyroid nodules, the ultrasound images serve as an essential tool to discriminate the malignant nodules from the benign ones. In this paper, the method of transfer learning is applied to classify the malignant and benign thyroid nodules based on their ultrasound images. The principal steps are preprocessing, data augmentation and classification by transfer learning. The preprocessing concentrates in extracting the region of interest (ROI). Two techniques of data augmentation are realized in our experiment, the traditional ways of augmenting images and a small convolutional network proposed by our own. After the augmentation of dataset, a pre-trained residual network is adopted to do transfer learning, and the parameters of this pre-trained net are fine-tuned with three different datasets that we have attained, including the original dataset, the augmented dataset via traditional methods and the augmented dataset via our convolutional network. The performances are then evaluated by three indexes, and the final results have proved the effectiveness of our convolutional augmentation network as well as the application of transfer learning. The best accuracy on the augmented dataset via convolutional network attains 93.75%, which exceeds the results of other two datasets and in the meanwhile outperforms other relevant methods.
A soft, bistable valve for autonomous control of soft actuators

An entirely soft valve uses a snap-through instability to integrate autonomous control functions into soft actuators. Almost all pneumatic and hydraulic actuators useful for mesoscale functions rely on hard valves for control. This article describes a soft, elastomeric valve that contains a bistable membrane, which acts as a mechanical “switch” to control air flow. A structural instability—often called “snap-through”—enables rapid transition between two stable states of the membrane. The snap-upward pressure, ΔP1 (kilopascals), of the membrane differs from the snap-downward pressure, ΔP2 (kilopascals). The values ΔP1 and ΔP2 can be designed by changing the geometry and the material of the membrane. The valve does not require power to remain in either “open” or “closed” states (although switching does require energy), can be designed to be bistable, and can remain in either state without further applied pressure. When integrated in a feedback pneumatic circuit, the valve functions as a pneumatic oscillator (between the pressures ΔP1 and ΔP2), generating periodic motion using air from a single source of constant pressure. The valve, as a component of pneumatic circuits, enables (i) a gripper to grasp a ball autonomously and (ii) autonomous earthworm-like locomotion using an air source of constant pressure. These valves are fabricated using straightforward molding and offer a way of integrating simple control and logic functions directly into soft actuators and robots.
Strategies for the prevention of postoperative pulmonary complications

A recent retrospective observational database analysis of 109,360 patient records reported that postoperative pulmonary complications were associated with pressurecontrolled ventilation (PCV) as compared with volume-controlled ventilation (VCV) [1]. Furthermore, PCV was associated with higher tidal volumes and driving pressures, and postoperative pulmonary complications with PCV were more common at lower values of positive endexpiratory pressure (PEEP). The authors therefore advocate for the use of VCV, an appropriate level of PEEP and low driving pressures to reduce postoperative pulmonary complications [1]. Their methods, results and conclusions have attracted much attention [2, 3] and we believe several aspects of their study warrant further discussion. Although there is good evidence supporting the theory that intra-operative high tidal volumes, high driving pressures and low or no PEEP increase the risk of postoperative pulmonary complications [4–6], there is no clinical evidence or biological rationale as to why PCV alone should be any riskier than VCV [7]. Our interpretation is the association described may be due to ventilatory parameters such as tidal volume, driving pressure and PEEP rather than the mode of ventilation itself. We also argue the mode of mechanical ventilation is less important than other ventilatory and nonventilatory aspects of peri-operative care. In this editorial we set out why we take this stance, explore some definitional and methodological issues arising from the study, and set the findings in their clinical context.
Serotonergic modulation of hippocampal pyramidal cells in euthermic, cold-acclimated, and hibernating hamsters.

Serotonergic fibers project to the hippocampus, a brain area previously shown to have distinctive changes in electroencephalograph (EEG) activity during entrance into and arousal from hibernation. The EEG activity is generated by pyramidal cells in both hibernating and nonhibernating species. Using the brain slice preparation, we characterized serotonergic responses of these CA1 pyramidal cells in euthermic, cold-acclimated, and hibernating Syrian hamsters. Stimulation of Shaffer-collateral/commissural fibers evoked fast synaptic excitation of CA1 pyramidal cells, a response monitored by recording population spikes (the synchronous generation of action potentials). Neuromodulation by serotonin (5-HT) decreased population spike amplitude by 54% in cold-acclimated animals, 80% in hibernating hamsters, and 63% in euthermic animals. The depression was significantly greater in slices from hibernators than from cold-acclimated animals. In slices from euthermic animals. changes in extracellular K+ concentration between 2.5 and 5.0 mM did not significantly alter serotonergic responses. The 5-HT1A agonist 8-hydroxy-2(di- n-propylamino)tetralin mimicked serotonergic inhibition in euthermic hamsters. Results show that 5-HT is a robust neuromodulator not only in euthermic animals but also in cold-acclimated and hibernating hamsters.
Spine Image Fusion Via Graph Cuts

This study investigates a novel CT/MR spine image fusion algorithm based on graph cuts. This algorithm allows physicians to visually assess corresponding soft tissue and bony detail on a single image eliminating mental alignment and correlation needed when both CT and MR images are required for diagnosis. We state the problem as a discrete multilabel optimization of an energy functional that balances the contributions of three competing terms: (1) a squared error, which encourages the solution to be similar to the MR input, with a preference to strong MR edges; (2) a squared error, which encourages the solution to be similar to the CT input, with a preference to strong CT edges; and (3) a prior, which favors smooth solutions by encouraging neighboring pixels to have similar fused-image values. We further introduce a transparency-labeling formulation, which significantly reduces the computational load. The proposed graph-cut fusion guarantees nearly global solutions, while avoiding the pix elation artifacts that affect standard wavelet-based methods. We report several quantitative evaluations/comparisons over 40 pairs of CT/MR images acquired from 20 patients, which demonstrate a very competitive performance in comparisons to the existing methods. We further discuss various case studies, and give a representative sample of the results.