Miracle-dz/UniFAR-FTUs huggingface dataset:
FLEX: A Parametric Study of Its Tandem Formation With Sentinel-3

The Fluorescence Explorer (FLEX) is an Earth observation mission currently in development by the European Space Agency to perform quantitative measurements of the solar induce vegetation fluorescence. As a core of the mission concept, FLEX is planned to be launched by the end of 2023 and shall fly in tandem with one of the Copernicus Sentinel-3 satellites, which is already in orbit. This situation will allow FLEX to benefit from the optical and thermal sensors of Sentinel-3 and provide an integrated package of measurements. This paper presents the preliminary parametric analysis on the along-track dynamic of the tandem flight formation between Sentinel-3 and FLEX. It includes the study of the maneuvering strategy for a master–slave scenario concept, where Sentinel-3 acts as the master of the formation, whereas FLEX is the slave. This control strategy is assessed in terms of safety for both satellites and performance, where it is of interest to maintain the along-track distance between satellites as bounded as possible. Numerical and analytical results of this paper are provided showing that the control strategy proposed is able to fulfill the mission requirements under the expected conditions while providing enough time for the control center to coordinate the orbital maneuvers of Sentinel-3 and FLEX. Additionally, and from the results obtained in this paper, it is concluded that the safest configuration for the mission is locating FLEX ahead of Sentinel-3.
Secure Federated Learning With Fully Homomorphic Encryption for IoT Communications

The emergence of the Internet of Things (IoT) has revolutionized people’s daily lives, providing superior quality services in cognitive cities, healthcare, and smart buildings. However, smart buildings use heterogeneous networks. The massive number of interconnected IoT devices increases the possibility of IoT attacks, emphasizing the necessity of secure and privacy-preserving solutions. Federated learning (FL) has recently emerged as a promising machine learning (ML) paradigm for IoT networks to address these concerns. In FL, multiple devices collaborate to learn a global model without sharing their raw data. However, FL still faces privacy and security concerns due to the transmission of sensitive data (i.e., model parameters) over insecure communication channels. These concerns can be addressed using fully homomorphic encryption (FHE), a powerful cryptographic technique that enables computations on encrypted data without requiring them to be decrypted first. In this study, we propose a secure FL approach in IoT-enabled smart cities that combines FHE and FL to provide secure data and maintain privacy in distributed environments. We present four different FL-based FHE approaches in which data are encrypted and transmitted over a secure medium. The proposed approaches achieved high accuracy, recall, precision, and F-scores, in addition to providing strong privacy and security safeguards. Furthermore, the proposed approaches effectively reduced communication overhead and latency compared to the baseline approach. These approaches yielded improvements ranging from 80.15% to 89.98% in minimizing communication overhead. Additionally, one of the approaches achieved a remarkable latency reduction of 70.38%. The implementation of these security models is nontrivial, and the code is publicly available at https://github.com/Artifitialleap-MBZUAI/Secure-Federated-Learning-with-Fully-Homomorphic-Encryption-for-IoT-Communications.
Unveiling the identity of Diaurora Cockerell, 1903 (Bivalvia, Unionidae): morphology, molecular phylogenetics, and the description of a new species

﻿Abstract The monotypic freshwater mussel genus Diaurora Cockerell, 1903 has long been enigmatic due to its rarity and morphological confusion with Acuticosta. In this study, we comprehensively redescribed Diauroraaurorea (Heude, 1883) through a detailed analysis of shell morphology and molecular phylogenetics of recently collected specimens. Moreover, a new species, Diauroralaevesp. nov., was identified from the Fuyishui River, a tributary of the Zishui River in Shaoyang County, Shaoyang City, Hunan Province, China. Molecular phylogenetic analyses showed that D.aurorea and D.laevesp. nov. were reciprocally monophyletic and formed a clade as sister to Schistodesmus. Our study underscores the necessity of further exploring the diversity of freshwater mussels in understudied small tributaries throughout China.
Potential Harm of IQOS Smoke to Rat Liver

The Food and Drug Administration has recently classified the IQOS electronic cigarette as a modified-risk tobacco product. However, IQOS cigarettes still release various harmful constituents typical of conventional cigarettes (CCs), although the concentrations are markedly lower. Here, we investigated the damaging effects of IQOS smoking on the liver. Male Sprague Dawley rats were exposed, whole body, 5 days/week for 4 weeks to IQOS smoke (4 sticks/day), and hepatic xenobiotic metabolism, redox homeostasis and lipidomic profile were investigated. IQOS boosted reactive radicals and generated oxidative stress. Exposure decreased cellular reserves of total glutathione (GSH) but not GSH-dependent antioxidant enzymes. Catalase and xanthine oxidase were greater in the exposed group, as were various hepatic CYP-dependent monooxygenases (CYP2B1/2, CYP1A1, CYP2A1, CYP2E1-linked). Respiratory chain activity was unaltered, while the number of liver mitochondria was increased. IQOS exposure had an impact on the hepatic lipid profile. With regard to the expression of some MAP kinases commonly activated by CC smoking, IQOS increased the p-p38/p38 ratio, while erythroid nuclear transcription factor 2 (Nrf2) was negatively affected. Our data suggest that IQOS significantly impairs liver function, supporting the precautionary stance taken by the WHO toward the use of these devices, especially by young people and pregnant women.
Wide Range Achievement Test 4

This machine consists primarily of a frame, which is supported by wheels, and the frame supports three spaced-apart self-placing form units, which operate in conjunction with finishing rollers. The self-placing form units of the machine are faced with endless synthetic rubber belts, which are backed up by hinged steel pads, and the top and bottom of the self-placing form units are sealed with a plate having a lip at the edge, to overlap the synthetic rubber, so as to repel any foreign matter, or concrete mix, from entering the inside of the units. The machine is reversible in direction when desired, and is used for concrete curb and gutter construction.
Psychopathic traits and altered resting-state functional connectivity in incarcerated adolescent girls

Previous work in incarcerated boys and adult men and women suggest that individuals scoring high on psychopathic traits show altered resting-state limbic/paralimbic, and default mode functional network properties. However, it is unclear whether similar results extend to high-risk adolescent girls with elevated psychopathic traits. This study examined whether psychopathic traits [assessed via the Hare Psychopathy Checklist: Youth Version (PCL:YV)] were associated with altered inter-network connectivity, intra-network connectivity (i.e., functional coherence within a network), and amplitude of low-frequency fluctuations (ALFFs) across resting-state networks among high-risk incarcerated adolescent girls (n = 40). Resting-state networks were identified by applying group independent component analysis (ICA) to resting-state fMRI scans, and a priori regions of interest included limbic, paralimbic, and default mode network components. We tested the association of psychopathic traits (PCL:YV Factor 1 measuring affective/interpersonal traits and PCL:YV Factor 2 assessing antisocial/lifestyle traits) to these three resting-state measures. PCL:YV Factor 1 scores were associated with increased low-frequency and decreased high-frequency fluctuations in components corresponding to the default mode network, as well as increased intra-network FNC in components corresponding to cognitive control networks. PCL:YV Factor 2 scores were associated with increased low-frequency fluctuations in sensorimotor networks and decreased high-frequency fluctuations in default mode, sensorimotor, and visual networks. Consistent with previous analyses in incarcerated adult women, our results suggest that psychopathic traits among incarcerated adolescent girls are associated with altered intra-network ALFFs—primarily that of increased low-frequency and decreased high-frequency fluctuations—and connectivity across multiple networks including paralimbic regions. These results suggest stable neurobiological correlates of psychopathic traits among women across development.
Chronic Toxicity Tests with Daphnia magna for the Examination of River Water Quality

− 19 − ABSTRACT The toxicological effects of river water on the reproduction of the water f lea Daphnia magna were assessed with the standard 21-d chronic test(OECD TG211)at four river sites(St. 1–4)in rural districts of the Kanto Plain(Ibaraki Prefecture, Japan) at monthly intervals from April 2007 to March 2010. Over the 3 years, we recorded the following average numbers of live D. magna offspring after the 21-d tests: 17–233, 14–223, 29–210, and 84–209 in St. 1, 2, 3, and 4, respectively. The average numbers in August 2007, May and September 2008, and April 2009 at St. 1; August 2007 and May 2008 at St. 2, and June 2007 and April 2009 at St. 3 were significantly lower than those of the control(ANOVA, P < 0.01). The results of the above tests suggest that D. magna may be affected not only by the overall pesticide toxicity in the river water, but also by other factors that were not clarified in the present study. In addition, significant positive correlations were observed at each site between the body length of D. magna and the total number of offspring at 7 d(r = 0.783), 14 d(r = 0.772), and 21 d(r = 0.931)after the test began on 10 May 2008. These findings suggest that the body length of D. magna might be used to evaluate the toxicological effects of river water, even at 7 d, by using the standard chronic toxicity test.
USE OF BIOLOGICAL ORGANIC FERTILIZERS AND PESTICIDES TO IMPROVE POTATO CULTIVATION IN SLOPE ANDISOLS

In the 1990s, potato yield in the Andisols of Dieng, Central Java, Indonesia, was approximately 30 t ha–1, but this value decreased rapidly to 12–15 t ha–1 in recent years. This rapid decline could be attributed to the use of unbalanced organic and chemical fertilizers, without the application of conservation techniques. Therefore, this study aimed to sustainably improve the local potato cultivation pattern of farmers on Andisols using biological organic fertilizers and pesticides (BOFP). A randomized block design was used with two factors, namely: 1) 20 t BOFP, 300 kg Urea, 500 kg SP 36, 300 kg KCl, and 200 kg lime ha–1, and 2) comparison with the pattern of farmers, consisting of 20 t of chicken manure, 1–t NPK, and 250 kg ZA ha–1. The potato plant mounds were tilted 10% to the contour direction, and each treatment was carried out with 16 replications. Granola seeds were used to plant potato during the rainy season from March-June 2022. The results showed that the plants cultivated using the local pattern of farmers were affected by wilt from Fusarium spp, while the use of BOFP decreased the incidence of the disease by 80%. Furthermore, the BOFP pattern significantly increased Andisols organic-C from 1.78% to 3.83% and total soil P from 5.20% to 11.34%, compared to the pattern of farmers. It also increased potato yields from 12.31 t ha–1 to 22.93 t ha–1 and the R/C from 0.85 to 1.23, compared to the pattern of farmers. Based on the results, the use of BOFP pattern decreased wilt attacks by Fusarium spp, improved the productivity of Andisols, as well as increased potato production and profits of farmers.
The Diagnostic Accuracy of N-Terminal Pro-B-Type Natriuretic Peptide and Soluble ST2 for Heart Failure in Chronic Kidney Disease Patients: A Comparative Analysis

Background N-terminal proatrial natriuretic peptide (NT-proBNP) levels are often markedly elevated in patients with chronic kidney disease (CKD). Identifying novel biomarkers is an important step toward effective diagnosis. Interleukin-1 receptor-like 1 (IL1RL1) protein and human/Soluble suppression of tumorigenesis-2 (sST2) are promising biomarkers for heart failure (HF). This study aimed to assess the trend of NT-proBNP and sST2 in chronic kidney disease and their diagnostic value for HF. Material/Methods This study was carried out on 420 patients who were divided into a no heart failure group (N=182) and a heart failure group (N=238). Spearman correlation analysis was used to test the association of sST2 and NT-proBNP with renal function. The diagnostic value of each biomarker was assessed using receiver operating characteristic (ROC) curves according to 3 different forms: Total group (n=420), non-CKD group (n=217), and CKD group (n=203). Results A striking correlation between eGFR and NT-proBNP (r=−0.525; P<0.001) seemed to be far stronger than that with sST2 (r=−0.147; P<0.05). The optimum cutoff points for sST2 and NT-proBNP to detect HF were 28.960 ng/mL and 1280 pg/mL, respectively, in total, 28.71 ng/mL and 481 pg/mL, respectively, in non-CKD patients, and 30.55 ng/mL and 3314 pg/mL, respectively, in CKD patients. The combined model of sST2 and NT-proBNP was superior to the model of sST2 or NT-proBNP alone, and the difference was statistically significant (P<0.05). Conclusions The diagnostic value of sST2 is less affected by decreased renal function. sST2 combined with NT-proBNP may improve the diagnostic accuracy of HF.
Marxist Philosophy in The Selected Poems of Brecht and Naaz Khialvi: A Comparative Critique

Though a comparative study opens up new horizons of knowledge and a vast body of literature has been published on Marxism from the perspective of comparative study but a Marxist analysis of Brecht as compared with Pakistani Urdu poet, Naaz Khialvi, has not yet been accomplished. Marxism is a theory and a method originated from the work of Marx and Engels to analyze and critique the capitalism that produced social conflict and class struggles. The present study is qualitative in nature and it uses research methodology of comparative study. The findings of this study are: i. exploration of the exploitation of the poor class; ii. reflection of Marxist inclinations in the selected poems of Brecht and Khialvi. The objective of this study is to compare the marginalized Pakistani Urdu poet Khialvi from the perspective of Pakistani capitalist society with the mainstream Marxist poet and playwright Brecht.
Clinical Features and Outcomes of Acute Kidney Injury in Critically Ill COVID-19 Patients: A Retrospective Observational Study

Background: An alarming number of COVID-19 patients, especially in severe cases, have developed acute kidney injury (AKI). Aim: The study aimed to assess the frequency, risk factors, and impact of AKI on mortality in critically ill COVID-19 patients. Methods: The study was a retrospective observational study conducted in the MICU. Univariate and multivariate analyses were performed to identify risk factors for AKI and clinical outcomes. Results: During the study period, 465 consecutive COVID-19 patients were admitted to the MICU. The patients’ characteristics were median age, 64 [54–71] years; median SAPSII, 31 [24–38]; and invasive mechanical ventilation (IMV), 244 (52.5%). The overall ICU mortality rate was 49%. Two hundred twenty-nine (49.2%) patients developed AKI. The factors independently associated with AKI were positive fluid balance (OR, 2.78; 95%CI [1.88–4.11]; p < 0.001), right heart failure (OR, 2.15; 95%CI [1.25–3.67]; p = 0.005), and IMV use (OR, 1.55; 95%CI [1.01–2.40]; p = 0.044). Among the AKI patients, multivariate analysis identified the following factors as independently associated with ICU mortality: age (OR, 1.05; 95%CI [1.02–1.09]; p = 0.012), IMV use (OR, 48.23; 95%CI [18.05–128.89]; p < 0.001), and septic shock (OR, 3.65; 95%CI [1.32–10.10]; p = 0.012). Conclusion: The present study revealed a high proportion of AKI among critically ill COVID-19 patients. This complication seems to be linked to a severe cardiopulmonary interaction and fluid balance management, thus accounting for a poor outcome.
Small Molecules with Thiourea Skeleton Induce Ethylene Response in Arabidopsis

Ethylene is the only gaseous plant hormone that regulates several aspects of plant growth, from seedling morphogenesis to fruit ripening and organ senescence. Ethylene also stimulates the germination of Striga hermonthica, a root parasitic weed that severely damages crops in sub-Saharan Africa. Thus, ethylene response stimulants can be used as weed and crop control agents. Ethylene and ethephon, an ethylene-releasing compound, are currently used as ethylene response inducers. However, since ethylene is a gas, which limits its practical application, we targeted the development of a solid ethylene response inducer that could overcome this disadvantage. We performed chemical screening using Arabidopsis thaliana “triple response” as an indicator of ethylene response. After screening, we selected a compound with a thiourea skeleton and named it ZKT1. We then synthesized various derivatives of ZKT1 and evaluated their ethylene-like activities in Arabidopsis. Some derivatives showed considerably higher activity than ZKT1, and their activity was comparable to that of 1-aminocyclopropane-1-carboxylate. Mode of action analysis using chemical inhibitors and ethylene signaling mutants revealed that ZKT1 derivatives activate the ethylene signaling pathway through interactions with its upstream components. These thiourea derivatives can potentially be potent crop-controlling chemicals.
Macroeconomic Impact of the Supply Shock during COVID-19 Pandemic in India

The study focuses on examining the impact of the COVID-19 supply shock on the Indian macroeconomic variables. Time Varying Factor Augmented Vector Auto Regressive Model (TVP-FAVAR) has been employed for the econometric analysis. We found that with supply shock, retail food inflation outpaced in COVID times. Production levels reported by IIP fell to abysmally low levels in the post-COVID times, when the economy stalled. The liquidity stimulus provided by the central bank led to the negative response of policy rates to the supply shocks during the COVID times. The paper suggests the central bank to focus on sector-specific liquidity injections and take appropriate steps to evacuate fluctuating generic liquidity in the Indian economic system. This will reduce food inflation and help small non-food related industries to bounce back.
Remarks on thermalization in 2D CFT

We revisit certain aspects of thermalization in 2D conformal field theory (CFT). In particular, we consider similarities and differences between the time dependence of correlation functions in various states in rational and non-rational CFTs. We also consider the distinction between global and local thermalization and explain how states obtained by acting with a diffeomorphism on the ground state can appear locally thermal, and we review why the time-dependent expectation value of the energy-momentum tensor is generally a poor diagnostic of global thermalization. Since all 2D CFTs have an infinite set of commuting conserved charges, generic initial states might be expected to give rise to a generalized Gibbs ensemble rather than a pure thermal ensemble at late times. We construct the holographic dual of the generalized Gibbs ensemble and show that, to leading order, it is still described by a Banados-Teitelboim-Zanelli black hole. The extra conserved charges, while rendering c < 1 theories essentially integrable, therefore seem to have little effect on large-c conformal field theories.
Multileader Multiagent Systems Containment Control With Event-Triggering

This paper studies the event-triggered containment control (CC) problem of multiagent systems with a directed graph, where the followers’ communication graph is an undirected graph. A novel event-triggered CC protocol is presented to schedule communications between agents, which depends on both local states and control inputs. Different from traditional approaches using broadcasts, a unique property of the proposed protocol is that it enables agent-to-agent data transmission. To do so, each communication link is associated with a specific local event. The estimated relative interagent states are transmitted over a specific link only when the related input-based event is detected. We develop sufficient conditions to solve CC problem under this protocol and extend it to the adaptive event-triggered protocol that does not require the global knowledge on the smallest positive eigenvalue of the Laplacian. For both protocols, we derive positive low bounds on the interevent time intervals generated by individual events, which eliminate the “Zeno phenomenon. ” Feasibility of the proposed algorithm is verified by an example.
Imputing Trip Purpose Based on GPS Travel Survey Data and Machine Learning Methods

In the recent decades, increasing number of travel researchers show interest in travel behavior research based on GPS/GIS technology. The challenge of successfully utilizing GPS-based data is the efficient post-processing method that could generate the essential components as accurately as possible in travel behavior researches such as travel time, trip purpose, travel mode, and trip length. This paper concentrates on part of the GPS data post-processing: trip purpose derivation, and explores the feasibility of automating trip purpose detection employing machine learning method with geospatial location data, the land use data, and the in-practice GPS-based survey conducted by University of Minnesota. Furthermore, it evaluates the impacts of different land use coding methods based on polygon-level, geo-coded home/work locations and Point of Interest (POI) land use data combined with different machine learning methods including decision tree, support vector machine and metalearner. A heterogeneous sample of 2238 trip records with decoded 7 trip purposes is employed. Results show that under all the machine learning methods, the cluster-based land use coding method is exceeded by the closest POI land use coding method, while amongst the three machine learning methods, the metalearner has the best performance to classify the trip purpose. Based on the metalearner and the data set using the closest POI land use coding method, the highest classification accuracy 80.5817% can be achieved.
Self-compassion and Trust as the Determinants of Pro-social Behavior: Moderating role of Gender among Adults

The study was aimed at analyzing Self-compassion and Trust as the Determinants of Pro-social Behavior. A correlational research design was used. Gender use as the moderating role among adults. The survey was performed to collect data. The sample was comprised of 400 participants selected by using a convenient sampling technique. Inferential statistics were used by employing Pearson Coefficient Correlation, Linear Regression, t-test for independent sample designs, and ANOVA to test hypotheses. The result showed a positive relation between trust, self-compassion and pro-social behavior. The result shows that self-compassion predicted social behavior significantly. There is a significant difference between males and females in self-compassion and pro-social behavior. Conversely, there is no significant difference in the trust level based on gender. The self-compassion, trust and pro-social behavior were significantly different concerning the education of the participants.