Miracle-dz/UniFAR-FTUs huggingface dataset:
Life satisfaction and its correlates among older cancer survivors: critical role of psychosocial factors

Dear Editor,IntroductionImprovements in early detection and treatment of cancerhave resulted in a growing number of aging cancer survi-vors. Currently, 60% of the 10 million cancer survivors inthe USA are older than 65 years [1]. Yet, research hasbeen scarce on mental health outcomes, especially satis-faction with life (SWL), in older cancer survivors (OCSs)[2]. A number of existing studies in this arena are limitedby a focus on a single cancer type such as breast cancer,small sample sizes, inclusion of people with very recentlydiagnosed cancer, and a lack of age-matched healthycomparison subjects (HCs) [1–3]. There are also prevalentassumptions that limit progress in our understanding ofpsychological well-being in this population, for example,that positive emotions are absent, dangerous, delusional,or trivial among people with life-threatening illnesses[4]. Studiessuggestthat OCSsfare muchworse physicallythan HCs as a result of adverse interactions among cancer,its treatment, aging, and comorbidity [1–3]. Findings onmental function suggest that OCSs have worse psycholog-ical functioning than HCs [1], experience age-associateddecline in health-related quality of life [5], and have loweroptimism about life expectancy than HCs [3]. Other ﬁnd-ings are mixed, with some studies reporting similar de-pression scores and cognitive function between OCSsand HCs [3], whereas others report increased depressionwith age but no association between age and SWL inOCSs [2]. Conversely, OCSs have reported resilient socialwell-being, spirituality, and personal growth with aging[6]. Notably, only a few reports have employedstandardized instruments for assessing positive psychoso-cialresourcessuchas SWL,resilience,optimism,personalmastery, and spirituality [2]. Thus,understandingSWLanditspsychosocialcorrelatesamong OCSs remains an important but understudied areawith high public health signiﬁcance. Such research wouldbe of value in developing interventions to increase SWL.The present study compared SWL, as well as health-related physical, cognitive, and psychosocial functioninginOCSs,withthatindemographicallymatchedHCsfroma community-based sample. As several studies havereported worse physical and psychological function inOCSs than among HCs [1], we hypothesized that OCSswould perform worse in all spheres of functioningcompared with HCs. We also examined the correlates ofSWL in the two groups.Materials and methodsParticipantsCancer survivors and HCs were recruited from a largemulticohortlongitudinal,community-basedsampleofolderadults whohad beenselected using random digit dialing, inthe Successful AGing Evaluation (SAGE) study. TheSAGEdataincludestandardizedmeasuresofphysical,cog-nitive,andpsychosocialfunctioningfromatelephoneinter-view and a mail-in survey completed by 1006 participantsbetween the ages of 50 and 99 years [7]. Two hundredandnineteenSAGEparticipantsreportedhavingadiagnosisof cancer (excluding skin cancer). They were comparedwith 219 age-, gender-, and education-matched HCs fromthe same sample, who did not report a history of cancer.
The Design of an Intelligent Pedometer Using Android

Google's Android has become the leading platform in smart phone market. Android has also integrated various sensors including gyroscope, orientation and accelerometer, so it is quite suitable to design mobile sensor applications.Pedometer is a common auxiliary device used formaintaining health and fitness. In this paper, an intelligent pedometer is developed using Android. The user's walking motion was detected via android sensor and pedometer application then analyzes the signal, calculates the walkingdistance and calories burned, and provides real time feedback to user via Bluetooth. The system provides three action modes: time-based mode, distance-based mode and count-based mode. All the tracking data are saved in SQLite database, and automatic threshold detection is used toimprove the accuracy.
Eigen-frequency analysis of spherical shell laminated composite plates with and without central cutouts using finite elements

This article presents the free vibration responses of spherical shell laminated composite panels (SSLCP) without and with central cutouts (square, circular and rectangular) using finite elements. The SSLCP midplane kinematics has been modeled using ABAQUS commercial finite element tool in the framework of first order shear deformation theory. Firstly, the validity of the present model is established by comparing the present natural frequencies values with the available benchmark results. Subsequently, the influence of both varying and constant aspect ratio for different central cutouts on the natural frequencies of SSLCP are investigated by solving appropriate numerical examples and findings are discussed in detail. The results are given in the form of tables and figures.
Desensitizing Mitochondrial Permeability Transition by ERK-Cyclophilin D Axis Contributes to the Neuroprotective Effect of Gallic Acid against Cerebral Ischemia/Reperfusion Injury

Ischemic stroke is a devastating disease with complex pathophysiology. Much evidence confirms that opening of the mitochondrial permeability transition pore (MPTP) is related with mitochondrial dysfunction to apoptosis in ischemic stroke, thus elucidating its signaling mechanism and screening novel MPTP inhibitor is therefore of paramount importance. Our earlier studies identified that gallic acid (GA), a naturally occurring plant phenol, endows with effect on inhibition of mitochondrial dysfunction, which has significant neuroprotective effect in cerebral ischemia/reperfusion injury. However, its molecular mechanisms regulating mitochondrial dysfunction remain elusive. Here, we uncover a role of GA in protecting mitochondria via MPTP inhibition. In addition to inhibit CypD binding to adenine nucleotide translocator, GA potentiates extracellular signal-regulated kinases (ERK) phosphorylation, leading to a decrease in cyclophilin D (CypD) expression, resulting in a desensitization to induction of MPTP, thus inhibiting caspase activation and ultimately giving rise to cellular survival. Our study firstly identifies ERK-CypD axis is one of the cornerstones of the cell death pathways following ischemic stroke, and confirms GA is a novel inhibitor of MPTP, which inhibits apoptosis depending on regulating the ERK-CypD axis.
Identifying Changes in Selective Constraints: Host Shifts in Influenza

The natural reservoir of Influenza A is waterfowl. Normally, waterfowl viruses are not adapted to infect and spread in the human population. Sometimes, through reassortment or through whole host shift events, genetic material from waterfowl viruses is introduced into the human population causing worldwide pandemics. Identifying which mutations allow viruses from avian origin to spread successfully in the human population is of great importance in predicting and controlling influenza pandemics. Here we describe a novel approach to identify such mutations. We use a sitewise non-homogeneous phylogenetic model that explicitly takes into account differences in the equilibrium frequencies of amino acids in different hosts and locations. We identify 172 amino acid sites with strong support and 518 sites with moderate support of different selection constraints in human and avian viruses. The sites that we identify provide an invaluable resource to experimental virologists studying adaptation of avian flu viruses to the human host. Identification of the sequence changes necessary for host shifts would help us predict the pandemic potential of various strains. The method is of broad applicability to investigating changes in selective constraints when the timing of the changes is known.
Confidence-based scoring: a useful diagnostic tool for detection tasks

This paper uses an unconventional analysis as a tool to diagnose the problems with three different speech activity detection systems. The unconventional analysis is to score the frames in an audio ﬁle in order of conﬁdence, starting with the frame that we have the most conﬁdence in and progressing towards less and less conﬁdent frames. By keeping track of the cumulative number of errors, we can determine how the errors are distributed across the data. Using speech activity detection on highly degraded audio as a case example, we show how this simple analysis can yield useful insight into both system performance and the data itself. In our case example, we use the analysis to establish three main points. First, a small percentage of the frames account for a lion’s share of the errors. Second, three different systems perform very poorly on the same small subset of data – despite the fact that the systems adopt very different decoding algorithms and features. In other words, three very different systems agree on which data is ‘hard’. Third, the ‘hard’ data is primarily characterized by its proximity to speech-nonspeech boundaries. Through follow-up analyses, we show that this phenomenon is not merely an artifact of ground truth inaccuracy, but rather a steady progression of the data becoming harder and harder to classify correctly as one moves closer to the boundaries. Through this case example, we demonstrate the utility of conﬁdence-based scoring as a general diagnostic tool for detection tasks on time-series data.
An Explanation of Nakamoto's Analysis of Double-spend Attacks

The fundamental attack against blockchain systems is the double-spend attack. In this tutorial, we provide a very detailed explanation of just one section of Satoshi Nakamoto's original paper where the attack's probability of success is stated. We show the derivation of the mathematics relied upon by Nakamoto to create a model of the attack. We also validate the model with a Monte Carlo simulation, and we determine which model component is not perfect.
Protruding Structures on Caterpillars Are Controlled by Ectopic Wnt1 Expression

Spine-like or protruding structures, which may be aposematic for predators, are often observed in multiple segments of lepidopteran larvae (caterpillars). For example, the larvae of the Chinese wheel butterfly, Byasa alcinous, display many protrusions on their backs as a warning that they are toxic. Although these protrusions are formed by an integument lined with single-layered epidermal cells, the molecular mechanisms underlying their formation have remained unclear. In this study, we focused on a spontaneous mutant of the silkworm, Bombyx mori, Knobbed, which shows similar protrusions to B. alcinous and demonstrates that Wnt1 plays a crucial role in the formation of protrusion structures. Using both transgene expression and RNAi-based knockdown approaches, we showed that Wnt1 designates the position where epidermal cells excessively proliferate, leading to the generation of knobbed structures. Furthermore, in the B. alcinous larvae, Wnt1 was also specifically expressed in association with the protrusions. Our results suggest that Wnt1 plays a role in the formation of protrusions on the larval body, and is conserved broadly among diverse species in Lepidoptera.
Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation

Given a corpus of news items consisting of images accompanied by text captions, we want to find out "who's doing what", i.e. associate names and action verbs in the captions to the face and body pose of the persons in the images. We present a joint model for simultaneously solving the image-caption correspondences and learning visual appearance models for the face and pose classes occurring in the corpus. These models can then be used to recognize people and actions in novel images without captions. We demonstrate experimentally that our joint 'face and pose' model solves the correspondence problem better than earlier models covering only the face, and that it can perform recognition of new uncaptioned images.
Ranking Automatically Generated Questions as a Shared Task

We propose a shared task for question generation: the ranking of reading comprehension questions about Wikipedia articles generated by a base overgenerating system. This task focuses on domain-general issues in question generation and invites a variety of approaches, and also permits semi-automatic evaluation. We describe an initial system we developed for this task, and an annotation scheme used in the development and evaluation of our system.
Robust control in closed loops realised by fast signal transmission of infinite gain neurons

We show that using recurrent networks with finite time constants is not contradictory to arbitrary fast signal transmission in a closed loop with appropriate feedbacks. This surprising result is due to the occurrence of infinitely amplifying subloops, which we formally describe by differential inclusions. The theory then shows that the transmission speed depends crucially on the gain of the transfer function. Generalising the theoretical framework we demonstrate how to build efficient, fast and robust neuro-controllers with pre-specified performance by application to the benchmark problem of balancing the inverted pendulum.
High-throughput monitoring of human tumor-specific T-cell responses with large peptide pools

In immune intervention trials, the comprehensive investigation of immunogenicity or T-cell epitope-mapping is challenging especially when a large set of epitopes needs to be screened and limited sample material is available. To this end, T-cell responses are often monitored using peptide pools. Here, we assessed the magnitude and sensitivity of detection of antigen-specific CD8+ and CD4+ T cells using a single peptide alone or mixed into large pools. Interestingly the magnitude of ex vivo anti-viral and anti-tumor T-cell responses was identical irrespective of the presence and number of irrelevant peptides, in different functional assays with PBMCs from healthy donors and cancer patients. Moreover, the presence of up to 300 irrelevant peptides did not affect the threshold of responsiveness of antigen-specific CD8+ T cells to single cognate peptides. These data demonstrate the relevance of using very large peptide pools for the sensitive and specific immune-monitoring of epitope-specific T cells in natural or immune-modulated context.
Identification of genes in the bW/bE regulatory cascade in Ustilago maydis

In the phytopathogenic fungus Ustilago maydis, the switch to filamentous growth and pathogenic development is controlled by a heterodimeric transcription factor consisting of the bW and bE homeodomain proteins. To identify genes in the regulatory cascade triggered by the bW/bE heterodimer, we have constructed strains in which transcription of the b genes is inducible by either arabinose or nitrate. At different time‐points after induction, genes that are switched on or off were identified through a modified, non‐radioactive RNA fingerprint procedure. From 348 gene fragments isolated initially, 48 fragments representing 34 different genes were characterized in more detail. After eliminating known genes, false positives and genes influenced in their expression profile by media conditions, 10 new b‐regulated genes were identified. Of these, five are upregulated and five are downregulated in presence of the b heterodimer. Two do not share significant similarity to database entries, whereas the other eight show similarity to disulphide isomerases, exochitinases, cation antiporters, plasma membrane (H+)‐ATPases, acyl transferases, a capsular associated protein of Cryptococcus neoformans, DNA polymerases X, as well as to a potential protein of Neurospora crassa. We demonstrate that in one of the early upregulated genes, the promoter can be bound by a bW/bE fusion protein in vitro. Interestingly, three out of the four genes that are downregulated by the b heterodimer appear upregulated after pheromone stimulation, suggesting a connection to the mating process.
Lipoprotein insulin resistance index: a lipoprotein particle-derived measure of insulin resistance.

UNLABELLED Abstract Background: Lipoprotein particle sizes and concentrations are characteristically altered in patients with insulin resistance (IR) or type 2 diabetes mellitus (T2DM). This study assessed the ability of an IR score, based on nuclear magnetic resonance (NMR)-derived lipoprotein information, to detect IR in otherwise healthy individuals. METHODS Lipoprotein subclass and size information were evaluated for strength of association with IR, as measured by homeostasis model assessment of insulin resistance (HOMA-IR) in the Multi-Ethnic Study of Atherosclerosis (MESA). To increase the likelihood of identifying subjects with IR, six lipoprotein measures were combined into a single algorithm. The resulting assay [Lipoprotein Insulin Resistance Index (LP-IR)] was developed using HOMA-IR in 4972 nondiabetic subjects from MESA and verified independently using glucose disposal rates (GDRs) measured during hyperinsulinemic-euglycemic clamps in 56 insulin-sensitive, 46 insulin-resistant, and 46 untreated subjects with T2DM. RESULTS LP-IR exhibited stronger associations with HOMA-IR (r=0.51) and GDR (r=-0.53) than each of the individual lipoprotein parameters as well as the triglycerides/high-density lipoprotein cholesterol (TGs/HDL-C) ratio (r=0.41 and -0.44, respectively). In MESA, associations between the LP-IR score and HOMA-IR were strong in men (r=0.51), women (r=0.52), European Americans (r=0.58), African Americans (r=0.48), Chinese Americans (r=0.49), and Hispanic Americans (r=0.45). When LP-IR was categorized by HOMA-IR and either body mass index (BMI) or fasting plasma glucose (FPG), subgroups were revealed whose LP-IR scores were high (≥ 50), despite having normal BMIs (<24 kg/m(2)) or FPG (<100 mg/dL). CONCLUSIONS LP-IR scores had strong associations with multiple measures, HOMA-IR, and GDR, the former being more reflective of hepatic and the latter of peripheral insulin sensitivity, and may represent a simple means to identify individuals with IR.
Wireless Passive Temperature Sensor Realized on Multilayer HTCC Tapes for Harsh Environment

A wireless passive temperature sensor is designed on the basis of a resonant circuit, fabricated on multilayer high temperature cofired ceramic (HTCC) tapes, and measured with an antenna in the wireless coupling way. Alumina ceramic used as the substrate of the sensor is fabricated by lamination and sintering techniques, and the passive resonant circuit composed of a planar spiral inductor and a parallel plate capacitor is printed and formed on the substrate by screen-printing and postfiring processes. Since the permittivity of the ceramic becomes higher as temperature rises, the resonant frequency of the sensor decreases due to the increasing capacitance of the circuit. Measurements on the input impedance versus the resonant frequency of the sensor are achieved based on the principle, and discussions are made according to the exacted relative permittivity of the ceramic and quality factor (Q) of the sensor within the temperature range from 19°C (room temperature) to 900°C. The results show that the sensor demonstrates good high-temperature characteristics and wide temperature range. The average sensitivity of the sensor with good repeatability and reliability is up to 5.22 KHz/°C. It can be applied to detect high temperature in harsh environment.
Two non-consecutive 24 h recalls using EPIC-Soft software are sufficiently valid for comparing protein and potassium intake between five European centres – results from the European Food Consumption Validation (EFCOVAL) study

The use of two non-consecutive 24 h recalls using EPIC-Soft for standardised dietary monitoring in European countries has previously been proposed in the European Food Consumption Survey Method consortium. Whether this methodology is sufficiently valid to assess nutrient intake in a comparable way, among populations with different food patterns in Europe, is the subject of study in the European Food Consumption Validation consortium. The objective of the study was to compare the validity of usual protein and K intake estimated from two non-consecutive standardised 24 h recalls using EPIC-Soft between five selected centres in Europe. A total of 600 adults, aged 45–65 years, were recruited in Belgium, the Czech Republic, France, The Netherlands and Norway. From each participant, two 24 h recalls and two 24 h urines were collected. The mean and distribution of usual protein and K intake, as well as the ranking of intake, were compared with protein and K excretions within and between centres. Underestimation of protein (range 2–13 %) and K (range 4–17 %) intake was seen in all centres, except in the Czech Republic. We found a fair agreement between prevalences estimated based on the intake and excretion data at the lower end of the usual intake distribution ( < 10 % difference), but larger differences at other points. Protein and K intake was moderately correlated with excretion within the centres (ranges = 0·39–0·67 and 0·37–0·69, respectively). These were comparable across centres. In conclusion, two standardised 24 h recalls (EPIC-Soft) appear to be sufficiently valid for assessing and comparing the mean and distribution of protein and K intake across five centres in Europe as well as for ranking individuals.
A Methodology Based on Mesh Morphing Algorithm and Improved Tabu Algorithm for Non-linear Inverse Scattering

This paper proposed an inversion method, for the study of non-linear inverse scattering problems, which is derived from an improved tabu algorithm and a mesh morphing technique based on finite-element method. A remesh-free morphing method is reported to improve the quality of the reconstruction with neither remeshing nor increases in the number of unknowns. Refined meshes can be quickly derived using a coordinate mapping technique according to a given fine mesh and an initial coarse mesh. The sensitivity analysis is used as an indication of the step vector to help obtain the global optimum rapidly, thus the proposed methodology is particularly useful for time consuming inverse problems. Numerical results both in 2-D and 3-D examples are given to showcase the efficiency and effectiveness of the proposed method.
H-LLL: using householder inside LLL

We describe a new LLL-type algorithm, H-LLL, that relies on Householder transformations to approximate the underlying Gram-Schmidt orthogonalizations. The latter computations are performed with floating-point arithmetic. We prove that a precision essentially equal to the dimension suffices to ensure that the output basis is reduced. H-LLL resembles the L2 algorithm of Nguyen and Stehlé that relies on a floating-point Cholesky algorithm. However, replacing Cholesky's algorithm by Householder's is not benign, as their numerical behaviors differ significantly. Broadly speaking, our correctness proof is more involved, whereas our complexity analysis is more direct. Thanks to the new orthogonalization strategy, H-LLL is the first LLL-type algorithm that admits a natural vectorial description, which leads to a complexity upper bound that is proportional to the progress performed on the basis (for fixed dimensions).