Miracle-dz/UniFAR-FTUs huggingface dataset:
Targeting the Host Mitochondria as a Novel Human Cytomegalovirus Antiviral Strategy

Human cytomegalovirus (HCMV) exploits host mitochondrial function to promote viral replication. HCMV gene products have been described to directly interact and alter functional or structural aspects of host mitochondria. Current antivirals against HCMV, such as ganciclovir and letermovir, are designed against viral targets. Concerns with the current antivirals include toxicity and viral resistance. Targeting host mitochondrial function is a promising alternative or complimentary antiviral approach as (1) drugs targeting host mitochondrial function interact with host targets, minimizing viral resistance, and (2) host mitochondrial metabolism plays key roles in HCMV replication. This review describes how HCMV alters mitochondrial function and highlights pharmacological targets that can be exploited for novel antiviral development.
A Collaborative Compression Scheme for Fast Activity Recognition on Mobile Devices via Global Compression Ratio Decision

Despite strong representation ability, deep convolutional neural networks (CNNs) are largely hindered in practical human activity recognition (HAR) deployment due to high computational cost, which is often unaffordable on resource-limited wearable devices. In this article, to bridge the gap between on-device HAR and deep learning, we present a collaborative compression scheme to reduce the runtime of HAR with an acceptable performance degradation, which combines channel pruning and tensor decomposition to simultaneously handle sparsity and low-rankness when fully considering mutual interference in one network consisting of efficient 1-dimensional convolutional kernels. Our method includes two main stages. Concretely, given a target compression ratio, a global compression ratio decision optimization is first performed to automatically decide per-layer compression ratio by measuring compression sensitivity, without requiring labor-exhaustive human intervention. Then a multi-step collaborative compression is iteratively implemented to remove the least important compression unit based on an improved importance metric until the per-layer target compression ratio is attained. Extensive experiments on multiple HAR benchmarks show that our approach considerably outperforms previous compression strategies. For example, it can achieve around 50% FLOPs reduction with only an accuracy drop of 0.25% and 0.15% on UCI-HAR and PAMAP2, respectively. Actual implementation is evaluated on an embedded platform.
Modelling of Climate Change’s Impact on Prunus armeniaca L.’s Flowering Time

This study presents the results of the development of numerical models for predicting the timing of apricot flowering, including using experimental data on the emergence of plants from a state of deep dormancy. The best results of approximation of the process of accumulation of the necessary cooling in the autumn–winter period were obtained using the sigmoidal function. Models that take into account the combined effect of temperature and photoperiod on the processes of spring development showed a high accuracy of the process of accumulation of thermal units. Based on the results of testing, two models were selected with an accuracy of 3.0 days for the start of flowering and the absence of a systematic bias, which can be considered a good quality assessment These models describe well the interannual variability of apricot flowering dates and can be used to predict these dates. The discrepancy is no more than 2–4 days in 87–89% of cases. Estimates of the timing of flowering and the end of deep dormancy are very important for increasing the profitability of fruit production in the South of Russia without incurring additional costs, by minimizing the risks associated with irrational crop placement and the selection of varieties without taking into account the specifics of climate change. When constructing a system of protective measures and dates of treatments, it is also necessary to take into account the calendar dates of the shift in the development of plants.
Novel Structural Properties and An Improved Bound for the Number Distinct Squares in a Strings

Combinatorics on words explore words – often called strings in the computer science community, or monoids in mathematics – and their structural properties. One of the most studied question deals with repetitions which are a form of redundancy. The thesis focuses on estimating the maximum number of distinct squares in a string of length n. Our approach is to study the combinatorial properties of these overlapping structures, nested systems, and obtain insights into the intricate patterns that squares create. Determining the maximum number of repetitions in a string is of interest in different fields such as biology and computer science. For example, the question arrises when one tries to bound the number of repetitions in a gene or in a computer file to be data compressed. Specific strings containing many repetitions are often of interest for additional combinatorial properties. After a brief review of earlier results and an introduction to the question of bounding the maximum number of distinct squares, we present the combinatorial insights and techniques used to obtain the main result of the thesis: a strengthening of the universal upper bound obtained by Fraenkel and Simpson in 1998.
Indoor and outdoor gamma radiation in Finland

This study measured the dose rate in air in the dwellings of 350 persons, selected randomly from the central population register of Finland. TLD dosemeters were employed for half-year measurements in 1991. Additionally, the results were compared with outdoor gamma radiation calculations based on data from a previous survey conducted in 1978-80. The absorbed dose rate in air in low-rise residential buildings and in blocks of flats had ranges of 24-144 nGy.h -1 and 45-184 nGy.h -1 , respectively, the population weighted mean values being 58 and 100 nGy.hs- 1 . The weighted mean for the total population was 73 nGy.h -1 . In the figures given, the dose rate due to cosmic radiation, 32 nGy.h -1 , was substracted. The population weighted mean trerrestrial dose rate outdoors was 71 nGy.h -1 . In houses and in flats the mean indoor/outdoor dose rate ratios were 0.84 and 1.33 respectively. This gave a population weighted mean for this ratio of 1.00. A statistically significant increase caused by the Chernobyl fallout was observed, these results being in agreement with shielding factor studies. This increment due to the Chernobyl fallout, which was substracted, was 0.3-19 nGy.h -1 , on average 3 nGy.h -1 . The national annual average effetive dose due to natural terrestrial radiation was 0.45 mSv and owing, in 1991, to the Chernobyl fallout 0.03 mSv
Multi-objective decision-theoretic planning

In most research on decision-theoretic agents, the desirability of actions and their effects is codified in a scalar reward function. However, many real-world decision problems have multiple objectives. In such cases the problem is more naturally expressed using a vector-valued reward function. Rather than having a single optimal policy, we then want to produce a set of policies that covers all possible preferences between the objectives. We call such a set a coverage set. In this dissertation, we focus on decision-theoretic planning algorithms that produce the Convex Coverage Set (CCS), which is the optimal solution set when either: 1) the user utility can be expressed as a weighted sum over the values for each objective; or 2) policies can be stochastic. We propose new methods based on two popular approaches to creating planning algorithms that produce an (approximate) CCS by building on an existing single-objective algorithm. In the inner loop approach, we replace the summations and maximizations in the inner most loops of the single-objective algorithm by cross-sums and pruning operations. In the outer loop approach, we solve a multi-objective problem as a series of scalarized problems by employing the single-objective method as a subroutine. Our most important contribution is an outer loop framework that we call Optimistic Linear Support (OLS). As an outer loop method OLS builds the CCS incrementally. We show that, contrary to existing outer loop methods, each intermediate result is a bounded approximation of the CCS with known bounds (even when the single-objective method used is a bounded approximate method as well) and is guaranteed to terminate in a finite number of iterations. We apply OLS-based algorithms to a variety of multi-objective decision problems, and show that it is more memory-efficient, and faster than corresponding inner loop algorithms for moderate numbers of objectives.
Family Preservation Strategies: Regendering Labor in Mixed-Status Marriage After Co-Deportation

Harsh U.S. deportation policies disproportionately target Latin American immigrant working-class men and subsequently divide families. The unique experiences of co-deported, mixed-status couples are missing from the depor-tation literature—that is, U.S. citizens, primarily women, who live outside of the United States with their deported Latin American immigrant spouses (what we call co-deportation) rather than living separately. Using hegemonic masculinity, this research qualitatively analyzes the experiences of eleven mixed-status couples internationally co-deported. Findings suggest couples’ gender dynamics shift paid and unpaid labor to sustain family life living as co-deportees. Co-deported couples are a testament to how adaptable heterosexual gender dynamics can be, but they also demonstrate the deep entrench-ment of hegemonic gender. This research provides implications for social workers advocating for transnational co-deported families.
Untangling the Association Between Goal Clarity and Public Service Motivation With the Moderating Role of Value Congruence

Drawing on the socialization aspect of public service motivation (PSM) and the internalization process of organizational values, this study empirically tests the argument that goal clarity leads to higher PSM, with a specific focus on the moderating role of value congruence between them. Using data from 4,133 Korean public employees in the 2021 Public Employee Perception Survey, the current study finds that individuals’ perception of goal clarity generally has a positive relationship with their PSM, especially among those who have high individual–organization value congruence. We also discovered that certain matched levels of both goal clarity and value congruence are crucial for the positive relationship between clear goal perception and PSM to exist. This study concludes that the relationship between goal clarity and PSM is not straightforward, but instead follows a U-shaped pattern, characterized by a decrease followed by an increase. This implies that perceiving clearer goals may have a demotivating effect on some employees; those with relatively low levels of goal clarity and, therefore, low goal congruence (i.e., lack of internalization of clear organizational goals) would instead be demotivated as they perceive clearer goals.
Deep Learning Network with Spatial Attention Module for Detecting Acute Bilirubin Encephalopathy in Newborns Based on Multimodal MRI

Background: Acute bilirubin encephalopathy (ABE) is a significant cause of neonatal mortality and disability. Early detection and treatment of ABE can prevent the further development of ABE and its long-term complications. Due to the limited classification ability of single-modal magnetic resonance imaging (MRI), this study aimed to validate the classification performance of a new deep learning model based on multimodal MRI images. Additionally, the study evaluated the effect of a spatial attention module (SAM) on improving the model’s diagnostic performance in distinguishing ABE. Methods: This study enrolled a total of 97 neonates diagnosed with ABE and 80 neonates diagnosed with hyperbilirubinemia (HB, non-ABE). Each patient underwent three types of multimodal imaging, which included T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and an apparent diffusion coefficient (ADC) map. A multimodal MRI classification model based on the ResNet18 network with spatial attention modules was built to distinguish ABE from non-ABE. All combinations of the three types of images were used as inputs to test the model’s classification performance, and we also analyzed the prediction performance of models with SAMs through comparative experiments. Results: The results indicated that the diagnostic performance of the multimodal image combination was better than any single-modal image, and the combination of T1WI and T2WI achieved the best classification performance (accuracy = 0.808 ± 0.069, area under the curve = 0.808 ± 0.057). The ADC images performed the worst among the three modalities’ images. Adding spatial attention modules significantly improved the model’s classification performance. Conclusion: Our experiment showed that a multimodal image classification network with spatial attention modules significantly improved the accuracy of ABE classification.
Clinico-Serological Profile of Infective Causes of Acute Hepatitis in Children Admitted to a Tertiary Care Centre

Background: Hepatitis is a major cause of healthcare burden in India. Hepatitis A is the most common cause of acute viral hepatitis in the pediatric population whereas hepatitis E virus (HEV) is the most important cause of epidemic hepatitis. Various other causes of acute infective hepatitis in children are dengue, malaria, and enteric fever. The aim of the present study is to understand the clinico-serological profile in cases of acute infective hepatitis in children. Methodology: The present study is a cross-sectional study that was carried out from 1 September 2017 to 31 March 2019. A total of 89 children in the age group 1-18 years with clinically suspected acute infective hepatitis and subsequent confirmation on laboratory tests were included in the study. Results: Hepatitis A (48.3%) was found to be the most common aetiology followed by dengue (22.5%) and hepatitis E (12.4%). No cases of hepatitis B or hepatitis C were found. The most common presenting complaint was fever (90%) and the most common clinical finding was icterus (69.7%). The sensitivity of icterus for the diagnosis of hepatitis was found to be 70%. Lab investigations showed a significant association between different etiologies of infective hepatitis with packed cell volume (PCV), white blood cell (WBC) count, and platelet count. Levels of aspartate aminotransferase (AST) and alanine transaminase (ALT) were raised in samples of patients with hepatitis A, hepatitis E, and combined hepatitis A and E infection as compared to other causes. All cases of hepatitis A and E were diagnosed with positive IgM antibody tests to the respective viral antigens. The most common complication was hepatic encephalopathy which was seen in patients with hepatitis A, dengue, and septicemia. Around 99% of patients recovered well and were discharged. One death occurred in a case of septicemia with septic shock with multiple organ dysfunction syndrome (MODS). Conclusion: The most common cause of infective hepatitis in children is hepatitis A. Other causes like dengue, malaria, and typhoid should also be kept in mind. The absence of icterus does not rule out hepatitis. Lab investigations including serology are important to confirm the diagnosis of various causes of hepatitis. Timely immunization against hepatitis is strongly recommended.
Influence of the Summer NAO on the Spring-NAO-Based Predictability of the East Asian Summer Monsoon

AbstractThe dominant mode of atmospheric circulation over the North Atlantic region is the North Atlantic Oscillation (NAO). The boreal spring NAO may imprint its signal on contemporaneous sea surface temperature (SST), leading to a North Atlantic SST tripolar pattern (NAST). This pattern persists into the following summer and modulates the East Asian summer monsoon (EASM). Previous studies have shown that the summer NAST is caused mainly by the preceding spring NAO, whereas the contemporaneous summer NAO plays a secondary role. The results of this study illustrate that, even if the summer NAO plays a secondary role, it may also perturb summer SST anomalies caused by the spring NAO. There are two types of perturbation caused by the summer NAO. If the spring and summer NAO patterns have the same (opposite) polarities, the summer NAST tends to be enhanced (reduced) by the summer NAO, and the correlation between the spring NAO and EASM is usually stronger (weaker). In the former (latter) case, the spring-NAO.
Nrf2-Mediated Pathway Activated by Prunus spinosa L. (Rosaceae) Fruit Extract: Bioinformatics Analyses and Experimental Validation

In our previous studies, Prunus spinosa fruit (PSF) ethanol extract was showed to exert antioxidant, antimicrobial, anti-inflammatory and wound healing activities. In the present study, an integrated bioinformatics analysis combined with experimental validation was carried out to investigate the biological mechanism(s) that are responsible for the reported PSF beneficial effects as an antioxidant during a pro-inflammatory TLR4 insult. Bioinformatics analysis using miRNet 2.0 was carried out to address which biological process(es) the extract could be involved in. In addition, Chemprop was employed to identify the key targets of nuclear receptor (NR) signaling and stress response (SR) pathways potentially modulated. The miRNet analysis suggested that the PSF extract mostly activates the biological process of cellular senescence. The Chemprop analysis predicted three possible targets for nine phytochemicals found in the extract: (i) ARE signaling, (ii) mitochondrial membrane potential (MMP) and (iii) p53 SR pathways. The PSF extract antioxidant effect was also experimentally validated in vitro using the human monocyte U937 cell line. Our findings showed that Nrf2 is modulated by the extract with a consequent reduction of the oxidative stress level. This was confirmed by a strong decrease in the amount of reactive oxygen species (ROS) observed in the PSF-treated cells subjected to lipopolysaccharide (LPS) (6 h treatment, 1 µg/mL). No visible effects were observed on p53 and MMP modulation.
Command filtered backstepping tracking control of uncertain nonlinear strict-feedback systems under a directed graph

This paper studies the distributed consensus tracking control problem of multiple uncertain non-linear strict-feedback systems under a directed graph. The command filtered backstepping approach is utilised to alleviate computation burdens and construct distributed controllers, which involves compensated signals eliminating filtered error effects in the design procedure. Neural networks are employed to estimate uncertain non-linear items. Using a Lyapunov stability theorem, it is proved that all signals in the closed-looped systems are semi-globally uniformly ultimately bounded. In addition, consensus errors converge to a small neighbourhood of the origin by adjusting the appropriate design parameters. Finally, simulation results are presented to demonstrate the effectiveness of the developed control design approach.
Mitigating anxiety: The role of strategic leadership groups during radical organisational change

This article examines the role of strategic leadership groups in radical organisational change. Previous research has focused on how ‘heroic’ individual leaders guide change. In contrast, we argue that strategic leadership groups are indispensable to understanding and supporting radical organisational change. Building on a longitudinal study in a global European company, our research identifies four phases of ‘negotiated order’ that shape group and organisational responses to change. Our findings reveal that strategic leadership groups help manage emotions and understand the shifting authority relations that inevitably arise during periods of change. Drawing upon the psychoanalytic concept of ‘projective identification’, we develop a theoretical framework for understanding the tensions of change. The model shows how emotional coalitions that develop in strategic leadership groups afford a source of political and psychological containment against the anxieties of radical organisational change. These formations offer transitional spaces for change, providing opportunities for progress. The advantage of this new perspective on radical change is that it helps to move the organisation beyond periods of ambivalence and conflict, with positive implications for leadership practice.
A Study of the Chemical Composition and Biological Activity of Michelia macclurei Dandy Heartwood: New Sources of Natural Antioxidants, Enzyme Inhibitors and Bacterial Inhibitors

The wood of Michelia macclurei Dandy (MD) is an excellent material that is widely used in the furniture, handicraft, and construction industries. However, less research has been conducted on the chemical composition and biological activity of heartwood, which is the main valuable part of the wood. This study aimed to investigate the chemical composition and biological activities of the heartwood of Michelia macclurei Dandy (MDHW) and to confirm the active ingredients. Triple quadrupole gas chromatography–mass spectrometry (GC-MS) was used to characterize the volatile components of MDHW, while ultra-performance liquid chromatography–mass spectrometry was used to analyze the non-volatile components (UPLC-MS). The total reducing power, 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical, and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) radical scavenging assays, acetylcholinesterase and α-glucosidase inhibition assays, and an antimicrobial test of 4 gram bacteria were used to describe the in vitro bioactivities. The GC-MS analysis showed that the volatile components of MDHW were mainly fatty compounds and terpenoids, with sesquiterpenes and their derivatives dominating the terpene composition. β-elemene was the main terpene component in the steam distillation (11.88%) and ultrasonic extraction (8.2%) methods. A total of 67 compounds, comprising 45 alkaloids, 9 flavonoids, 6 lignans, and others, were found by UPLC-MS analysis. The primary structural kinds of the non-volatile components were 35 isoquinoline alkaloids. Alkaloids were the predominant active constituent in all MDHW extracts, including crude extracts, alkaloid fractions, and non-alkaloid fractions. These extracts all demonstrate some biological effects in terms of antioxidant, enzyme inhibition, and bacterial inhibition. The findings of this study show that MDHW is abundant in chemical structure types, has great bioactivity assessment, and has the potential to be used to create natural antioxidants, products that postpone Alzheimer’s disease and lower blood sugar levels and antibacterial agents.
Inventory systems for perishable commodities with renewal input and Poisson output

We consider an inventory system to which arrival of items stored is a renewal process, and the demand is a Poisson process. Items stored have finite and fixed lifetimes. The blood-bank model inspired this study. Three models are studied. In the first one, we assume that each demand is for one unit and unsatisfied demands leave the system immediately. Using results on this model one is able to study a model in which arrival of items is Poisson but demands are for several units, and a model in which demands are willing to wait. We compute ergodic limits for the lost demands and the lost items processes and the limiting distribution of the number of items stored. The main tool in this analysis is an analogy to M/G/1 queueing systems with impatient customers.