Miracle-dz/UniFAR-FTUs huggingface dataset:
PSYCHOLOGICAL PROBLEMS

ANXIETY Anxiety is present to some degree or other in almost all patients with advanced cancer. To the patient the disease is a new experience for which he has no yardstick of normality. The carer’s knowledge of what may happen is vital to the anxious patient. Once having accepted the diagnosis of cancer a patient may attribute every new and trivial symptom to the cancer and assume that the condition is worsening. As a young patient dying of melanomatosis put it ‘the fear of cancer is worse than cancer’. Thus patients need to be listened to more than anything else, followed by detailed reassurance about their problems. Patients often want to know what may happen to them and turn to their carers as experts in death and dying to ask how they will end. Particular fears concern pain, choking in those who are dyspnoeic and severe haemorrhage in those who are bleeding. These questions can be difficult, particularly where the fear may be justified. Drug treatment of anxiety has earned itself a justifiably bad name as in the past it has often been found easier to prescribe than to listen and explain. However, anxiolytic drugs have a place in palliative care after appropriate listening and counselling. The choice of drug may depend on the patient’s other medication, which may include phenothiazines or hypnotics. Sometimes it may be more appropriate to adjust the dosage of other medication rather than prescribe additional anxiolytics. The benzodiazepines are among the most useful drugs. Diazepam may be given orally, rectally or intravenously and is rapid In action but does tend to sedate. Lorazepam is available for oral or intravenous administration and lorazepam tablets are absorbed rapidly sublingually. Opioids are probably the best anxiolytics.
Simulation of the folding equilibrium of α-helical peptides: A comparison of the generalized Born approximation with explicit solvent

We compare simulations using the generalized Born/surface area (GB/SA) implicit solvent model with simulations using explicit solvent (transferable intermolecular potential 3 point, TIP3P) to test the GB/SA algorithm. We use the replica exchange molecular dynamics method to sample the conformational phase space of two α-helical peptides, A21 and the Fs, by using two different classical potentials and both water models. We find that when using GB/SA: (i) A21 is predicted to be more helical than the Fs peptide at all temperatures; (ii) the native structure of the Fs peptide is predicted to be a helical bundle instead of a single helix; and (iii) the persistence length and most probable end-to-end distance are too large in the unfolded state when compared against the explicit solvent simulations. We find that the potential of mean force in the ϕψ plane is markedly different in the two solvents, making the two simulated peptides respond differently when the backbone torsions are perturbed. A fit of the temperature melting curves obtained in these simulations to a Lifson–Roig model finds that the GB/SA model has an unphysically large nucleation parameter, whereas the explicit solvent model produces values similar to experiment.
UNF-IDT: Automated Irony Detection in English Tweets

The usage of social media platforms has increased tremendously in the past decade. Twitter is one of the most popular platforms for sharing opinions and feelings on various topics, organizations rely on Twitter data to analyze and gather insights for their businesses using Natural Language Processing (NLP) techniques. However, there are various challenges in analyzing such a huge volume of tweets that are in text format. One such challenge is to identify irony in tweets, which has a significant impact on analyzing sentiments. To overcome this challenge, we propose a solution that automatically recognizes the presence of irony in text and classifies the type of irony. The solution consists of two tasks: Task A performs binary classification to annotate whether irony is expressed or not in each tweet, while Task B performs multi-class classification to classify the type of irony expressed in the tweets. We used the dataset from the “SemEval-2018 Task 3: Irony detection in English tweets” challenge to train and test the proposed solution. The dataset contains 3,817 English tweets for training and 784 English tweets for testing both Tasks A and B. We developed different machine learning models by leveraging traditional classifiers, neural networks, and large language models. Our UNF-IDT (Irony Detector in Text) model developed using BERT (Bidirectional Encoder Representations from Transformers) was able to achieve an F1 score of 0.757 for Task A (Binary Classification) and an F1 score of 0.449 for Task B (Multi-class Classification), retrospectively obtaining 4th and 9th ranks, in the two tasks respectively.
Stochastic Gradients Averaging for Federated Learning Algorithm with Compressed Quantization

Federated learning presents a promising avenue for training machine learning models across distributed edge networks. Given the inherent data heterogeneity and limited communication bandwidth stemming from the multitude of devices involved, the imperative of curtailing communication costs becomes apparent. While the compressed transmission model stands as a prevalent technique, it solely accommodates uniform data distributions, neglecting the influence of heterogeneous data. This study addresses the challenge by compressing the communication model between devices and the server, grounded in the implementation of stochastic gradient averaging to mitigate errors arising from data heterogeneity. Moreover, the algorithm’s convergence analysis is then provided for non-convex loss functions. The results show that our algorithm has the same convergence order as the stochastic controlled averaging federated learning algorithm. We validate our proposed algorithm using the MNIST and the CIFAR-100 datasets to determine its effectiveness.
Geochronology and geochemistry of early Paleozoic igneous rocks from the Zhangguangcai Range, northeastern China: Constraints on tectonic evolution of the eastern Central Asian Orogenic Belt

This study presents new geochronological and geochemical data for early Paleozoic igneous rocks of the Zhangguangcai Range, northeastern China, and uses these data to further define the early Paleozoic tectonic evolution of the Songnen–Zhangguangcai Range block (SZB) and the Jiamusi block, and provide insights into crustal growth and reworking processes in these blocks of the eastern Central Asian Orogenic Belt. New zircon U-Pb data indicate widespread early Paleozoic magmatism (ca. 516, 496–482, 475–461, and 426 Ma) in the southeastern SZB. The ca. 516 Ma magmatism formed Na-rich tonalites that contain low concentrations of rare earth elements, are enriched in Eu and Sr, have high CaO/Al2O3 and Ba/La ratios, low Rb/Sr and Rb/Ba ratios, and negative Ce anomalies and zircon εHf(t) values. These features suggest an origin from magmas generated by partial melting of ancient accumulated gabbroic rocks with the addition of subducted-sediment–derived fluids. The ca. 496–482 Ma magmatism formed calc-alkaline I-type biotite granodiorites and monzogranites, whereas the ca. 475–461 Ma igneous rocks include biotite monzogranites with K-rich adakitic signatures and alkali-feldspar granites. These ca. 496–461 Ma granitoids have zircon εHf(t) values from –0.82 to +5.44 and two-stage depleted-mantle model (TDM2) ages of 1490–1103 Ma, suggesting they formed from magmas generated by partial melting of heterogeneous Mesoproterozoic lower crustal material. The ca. 426 Ma Na-rich tonalites are geochemically similar to the ca. 516 Ma tonalites and also originated by partial melting of ancient gabbroic or amphibolitic rocks with the involvement of subducted-sediment–derived fluids. The geochemistry of these early Paleozoic igneous rock assemblages is indicative of formation in an active continental margin setting associated with northwestward subduction beneath the southeastern SZB. The zircon Hf isotopic compositions of these early Paleozoic igneous rocks indicate that Paleoproterozoic–Mesoproterozoic crustal material was reworked during the early Paleozoic subductionand collision-related tectonism. LITHOSPHERE; v. 9; no. 5; p. 803–827 | Published online 9 August 2017 https://doi.org/10.1130/L639.1
Impact of the 2002, Southern Hemisphere, stratospheric warming on the tropical cirrus clouds and convective activity

Tropical cirrus cloud variation associated with the southern hemisphere stratospheric sudden warming (SSW) in September 2002 was investigated using data from MODIS/Terra. During the SSW, enhanced wave forcings induced upwelling in the tropical stratosphere, which further extended into the equatorial troposphere. This initial perturbation of the tropospheric upwelling developed in the southern tropical troposphere through increased mass‐ and water vapor convergence in the lower level leading to deep convection. Cirrus cloud was first formed by the low temperature due to upwelling associated with the SSW, and it persisted for a few weeks after the end of SSW due to the low temperature associated with the Kelvin‐wave response to a deep convection triggered by the SSW.
Improved upper bounds for the mixed structured singular value

In this paper, we take a new look at the mixed structured singular value problem, a problem of finding important applications in robust stability analysis. Several new upper bounds are proposed using a very simple approach which we call the multiplier approach. These new bounds are convex and computable by using linear matrix inequality (LMI) techniques. We show, most importantly, that these upper bounds are actually lower bounds of a well-known upper bound which involves the so-called D-scaling (for complex perturbations) and G-scaling (for real perturbations).
A New 9-Level Modified Packed U-Cell Inverter

Packed U-cell (PUC) multilevel inverter (MLI) topology necessitates six switches, a dc source and a capacitor for 7-level output voltage. Similarly, for 9-level output voltage, PUC-MLI requires eight switches, a dc source and two capacitors. This paper proposes a new 9-level modified PUC-MLI with ten switches, a dc source and a capacitor. In proposed topology, though four switches are added to 7-level PUC-MLI, no extra capacitor is required. With this addition, the modified PUC -MLI can provide 9-level output voltage. Now, not only difference between the voltage of capacitor and dc source appears across the load, but also the sum of two voltages is appears across the load. Thus, the proposed topology is able to add two more voltage levels. The proposed 9-level modified PUC inverter is analyzed and switching table is developed. PSIM software based simulation study is carried validate the theoretical analysis of the proposed MLI topology.
A Graph-Based Recommendation Model Using Contrastive Learning for Inductive Scenario

Graph-based recommendation models, which utilize a user-item interaction graph whose edges represent users' preferences, are well known because of their effectiveness. However, many existing models are intrinsically transductive, meaning they can make recommendations only for users and items that exist in the training data. To solve this challenge, some researchers focus on recommendations in the inductive scenario where new users and new items emerge in the inference phase. In this paper, we explore the potential of contrastive learning for the inductive scenario to further improve recommendation accuracy. The situation where new users and new items emerge can be interpreted as a change in the interaction graph. Therefore, it is crucial to capture the change in the interaction graph for inductive recommendations. Based on the above perspective, we propose the contrastive learning framework, INductive Contrastive Learning (INCL). INCL creates an augmented graph by adding or removing edges of the original interaction graph and simulates changes in the interaction graph. By performing contrastive learning, INCL fosters each representation generated from the original interaction graph and the augmented graph to be similar. As a result, INCL is trained to generate robust representations that can adapt to changes in the interaction graph. Experimental results on real-world datasets demonstrate that INCL outperforms existing models in the inductive scenario, achieving up to 2.13% improvement in Recall@20.
Cross-architecture bug search in binary executables

Abstract With the general availability of closed-source software for various CPU architectures, there is a need to identify security-critical vulnerabilities at the binary level. Unfortunately, existing bug finding methods fall short in that they i) require source code, ii) only work on a single architecture (typically x86), or iii) rely on dynamic analysis, which is difficult for embedded devices. In this paper, we propose a system to derive bug signatures for known bugs. First, we compute semantic hashes for the basic blocks of the binary. When can then use these semantics to find code parts in the binary that behave similarly to the bug signature, effectively revealing code parts that contain the bug. As a result, we can find vulnerabilities, e.g., the famous Heartbleed vulnerabilities, in buggy binary code for any of the supported architectures (currently, ARM, MIPS and x86).
Effect of Chronic Pain on Fentanyl Self-Administration in Mice

The development of opioid addiction in subjects with established chronic pain is an area that is poorly understood. It is critically important to clearly understand the neurobiology associated with propensity toward conversion to addiction under conditions of chronic pain. To pose the question whether the presence of chronic pain influences motivation to self-administer opioids for reward, we applied a combination of rodent models of chronic mechanical hyperalgesia and opioid self-administration. We studied fentanyl self-administration in mice under three conditions that induce chronic mechanical hyperalgesia: inflammation, peripheral nerve injury, and repeated chemotherapeutic injections. Responding for fentanyl was compared among these conditions and their respective standard controls (naïve condition, vehicle injection or sham surgery). Acquisition of fentanyl self-administration behavior was reduced or absent in all three conditions of chronic hyperalgesia relative to control mice with normal sensory thresholds. To control for potential impairment in ability to learn the lever-pressing behavior or perform the associated motor tasks, all three groups were evaluated for acquisition of food-maintained responding. In contrast to the opioid, chronic hyperalgesia did not interfere with the reinforcing effect of food. These studies indicate that the establishment of chronic hyperalgesia is associated with reduced or ablated motivation to seek opioid reward in mice.
Towards Better Understanding of Domain Shift on Linear-Probed Visual Foundation Models

Visual foundation models have recently emerged to offer similar promise as their language counterparts: The ability to produce representations of visual data that can be successfully used in a variety of tasks and contexts. One common way this is shown in research literature is through “domain generalization” experiments of linear models trained from representations produced by foundation models (i.e. linear probes). These experiments largely limit themselves to a small number of benchmark data sets and report accuracy as the single figure of merit, but give little insight beyond these numbers as to how different foundation models represent shifts. In this work we perform an empirical evaluation that expands the scope of previously reported results in order to give better understanding into how domain shifts are modeled. Namely, we investigate not just how models generalize across domains, but how models may enable domain transfer. Our evaluation spans a number of recent visual foundation models and benchmarks. We find that not only do linear probes fail to generalize on some shift benchmarks, but linear probes trained on some shifted data achieve low train accuracy, indicating that accurate transfer of linear probes is not possible with some visual foundation models.
Echinococcus metacestode: in search of viability markers

Epidemiological studies have demonstrated that most humans infected with Echinococcus spp. exhibit resistance to disease. When infection leads to disease, the parasite is partially controlled by host immunity: in case of immunocompetence, the normal alveolar echinococcosis (AE) or cystic echinococcosis (CE) situation, the metacestode grows slowly, and first clinical signs appear years after infection; in case of impaired immunity (AIDS; other immunodeficiencies), uncontrolled proliferation of the metacestode leads to rapidly progressing disease. Assessing Echinococcus multilocularis viability in vivo following therapeutic interventions in AE patients may be of tremendous benefit when compared with the invasive procedures used to perform biopsies. Current options are F18-fluorodeoxyglucose-positron emission tomography (FDG-PET), which visualizes periparasitic inflammation due to the metabolic activity of the metacestode, and measurement of antibodies against recEm18, a viability-associated protein, that rapidly regresses upon metacestode inactivation. For Echinococcus granulosus, similar prognosis-associated follow-up parameters are still lacking but a few candidates may be listed. Other possible markers include functional and diffusion-weighted Magnetic Resonance Imaging (MRI), and measurement of products from the parasite (circulating antigens or DNA), and from the host (inflammation markers, cytokines, or chemokines). Even though some of them have been promising in pilot studies, none has been properly validated in an appropriate number of patients until now to be recommended for further use in clinical settings. There is therefore still a need to develop reliable tools for improved viability assessment to provide the sufficient information needed to reliably withdraw anti-parasite benzimidazole chemotherapy, and a basis for the development of new alternative therapeutic tools.
24‐Hour Changes in ACTH, Corticosterone, Growth Hormone, and Leptin Levels in Young Male Rats Subjected to Calorie Restriction

Calorie restriction of young male rats increases plasma prolactin, decreases luteinizing hormone (LH) and testosterone, and disrupts their 24 h secretory pattern. To study whether this could be the consequence of stress, we examined the 24 h variations of plasma adrenocorticotropic hormone (ACTH) corticosterone, growth hormone (GH), leptin, and adrenal corticosterone. Rats were submitted to a calorie restriction equivalent to a 66% of usual intake for 4 weeks, starting on day 35 of life. Controls were kept in individual cages and allowed to eat a normal calorie regimen. Significantly lower ACTH levels were detected in calorie‐restricted rats. Plasma corticosterone levels during the light phase of the daily cycle were significantly higher in calorie‐restricted rats. Time‐of‐day variation in plasma ACTH and corticosterone levels attained significance in calorie‐restricted rats only, with a maximum toward the end of the resting phase. The daily pattern of adrenal gland corticosterone mirrored that of circulating corticosterone; however, calorie restriction reduced its levels. Plasma ACTH and corticosterone correlated significantly in controls only. Calorie restriction decreased plasma GH and leptin, and it distorted 24 h rhythmicity. In a second study, plasma ACTH and corticosterone levels were measured in group‐caged rats, isolated control rats, and calorie‐restricted rats during the light phase of the daily cycle. Plasma ACTH of calorie‐restricted rats was lower, and plasma corticosterone was higher, compared with isolated or group‐caged controls. The changes in the secretory pattern of hormones hereby reported may be part of the neuroendocrine and metabolic mechanisms evolved to maximize survival during periods of food shortage.
Long-term tamoxifen therapy: can an antagonist become an agonist?

Antiestrogen administration is standard therapy for selected groups of women with breast cancer in the adjuvant setting (1). Large, well designed, randomized, controlled trials have confirmed the benefit of tamoxifen in extending both disease-free and overall survival when used for up to 5 yr (2). The question remains whether longer-term administration might produce even greater benefit. A major trial in the United States, the NSABP B-14 study, was designed to answer this question and compared 5 with 10 yr of tamoxifen administration. Recently (November 30, 1995) the National Cancer Institute mailed a Clinical Announcement to 22,000 physicians indicating that this study did not find 10 yr superior to 5 yr, and consequently women should receive tamoxifen for no more than 5 yr (3). Surprisingly, patients receiving tamoxifen for 10 yr experienced a shorter disease free survival than women given the drug for only 5 yr. This National Cancer Institute (NCI) announcement also reviewed a smaller unpublished Scottish trial showing nearly identical results. The Clinical Announcement commented that the “troublesome possibility that continuation of tamoxifen beyond 5 yr may actually be detrimental cannot be unequivocally resolved by these data. ” If a detrimental effect is ultimately substantiated, the question arises whether tamoxifen can be transformed from an antagonist to an estrogen agonist on breast cancer tissue with long-term use. Precedent for this phenomenon derives from studies in model systems of breast cancer. Tamoxifen is an antiestrogen initially utilized in the treatment of recurrent or advanced hormone-dependent breast cancer. Randomized clinical trials demonstrated efficacy equal to other hormonal therapies, a lack of significant side effects, and ease of administration. Additional trials then examined whether tamoxifen might be useful in the adjuvant setting to prevent or delay recurrence of breast cancer after initial surgical therapy. Meta-analyses of multiple studies comparing placebo with 2 yr of adjuvant tamoxifen clearly demonstrated benefit with extended disease-free survival as well as an increase in overall survival (2). The striking finding was that administration of tamoxifen for only two yr resulted in benefits to patients that lasted at least 15 yr. Seven percent more women receiving tamoxifen were alive 15 yr after starting therapy than those given placebo. These findings suggested that with nearly 200,000 women diagnosed with breast cancer per year, the number of lives saved with adjuvant tamoxifen could be substantial. The results of the 2 yr trials suggested the possibility that tamoxifen should be continued for a longer period. Com-
Analysis of inverse agonism at the δ opioid receptor after expression in Rat 1 fibroblasts

A cDNA encoding the mouse δ opioid receptor was expressed stably in a Rat 1 fibroblast cell line. Expression of this receptor was demonstrated both in ligand binding studies and by reverse transcriptase–PCR. In membranes of clone D2 cells the opioid peptide [-Ala#]-leucine enkephalin (DADLE) produced a robust, concentration-dependent, stimulation of basal high-affinity GTPase activity ; the prototypic opioid antagonist naloxone and the highly selective and potent δ opioid ligands H-Tyr-Tic-PhePhe-OH (TIPP) and H-Tyr-Tic[CH # -NH]Phe-Phe-OH (TIPP[ψ]) had little effect but N,N-diallyl-Tyr-Aib-Aib-Phe-Leu (ICI174864) caused a marked dose-dependent inhibition of this activity (Tic, 1,2,3,4-tetrahydroisoquinolin-2-yl-carbonyl ; Aib, α-aminobutyric acid). This effect of ICI174864 was reversed by TIPP[ψ] and attenuated after treatment of the cells with pertussis toxin. No stimulation by DADLE or inhibition by ICI174864 was observed in Rat 1 fibroblasts that did not express the δ opioid receptor. Basal binding of [$&S]guanosine 5«-O-(3-thiotriphosphate) to membranes of clone D2 cells was also stimulated by DADLE and inhibited by ICI174864; both of these effects were reversed by co-incubation with TIPP[ψ]. When cholera