Miracle-dz/UniFAR-FTUs huggingface dataset:
A High-Resolution Joint Angle-Doppler Estimation Sub-Nyquist Radar Approach Based on Matrix Completion

In order to reduce power consumption and save storage capacity, we propose a high-resolution sub-Nyquist radar approach based on matrix completion (MC), termed as single-channel sub-Nyquist-MC radars. While providing the high-resolution joint angle-Doppler estimation, this proposed radar approach minimizes the number of samples in all three dimensions, that is, the range dimension, the pulse dimension (also named temporal dimension), and the spatial dimension. In range dimension, we use a single-channel analog-to-information converter (AIC) to reduce the number of range samples to one; in both spatial and temporal dimensions, we employ a bank of random switch units to regulate the AICs, which greatly reduce the number of spatial-temporal samples. According to the proposed sampling scheme, the samples in digital processing center forwarded by M receive nodes and N pulses are only a subset of the full matrix of size M times N. Under certain conditions and with the knowledge of the sampling scheme, the full matrix can be perfectly recovered by using MC techniques. Based on the recovered full matrix, this paper addresses the problem of the high-resolution joint angle-Doppler estimation by employing compressed sensing (CS) techniques. The properties and performance of the proposed approach are demonstrated via simulations.
Variability of factors influencing coffee export performance in Indonesia.

Abstract Empirical evidence is lacking on the nexus between coffee commodity output and commodity price volatility of developing countries especially during pandemic era. The most visible impact from an economic perspective is the change of price expectation on people's basic needs which are in line with the decline of economic growth in Indonesia. This has significant implications, particularly considering the important role of coffee in supporting the country's economy. The aim of this study is to examine the factors that influence the performance of coffee exports in Indonesia. The novelty of this study lay on the used national dataset within the range of 20 years (2000-2020) and including the pandemic effect on coffee sector performance. We examines the relationship between variables and coffee exports in Indonesia using unit root tests, cointegration analysis, and an Error Correction Model (ECM). The results show that coffee exports, total area, coffee production, coffee price, gross national income, and coffee imports have significant influences on coffee exports. The variables of total area and coffee production impact coffee exports negatively in the long term, while coffee price, gross national income, and coffee imports have mixed effects. In the short term, total area and coffee production significantly affect coffee exports, while coffee prices and gross national income show no significant impact. Coffee imports have a significant negative influence on coffee exports in the short term. These findings contribute to understanding the dynamics of the coffee industry in Indonesia.
Orthostatic Hypotension in Multiple System Atrophy: Related Factors and Disease Prognosis

Background: Multiple system atrophy (MSA) is a rare neurodegenerative disease characterized by Parkinsonism, ataxia, and autonomic nervous failure. Orthostatic hypotension (OH) is the main feature of central vascular autonomic failure in MSA. Objective: The study aimed elucidate the effects of OH on cognitive function, disease milestones, and survival. Methods: A total of 444 patients with clinically established MSA were enrolled. Mild and severe OH were defined as a decrease in systolic blood pressure (SBP)/diastolic blood pressure (DBP) >20/10 mmHg and SBP/DBP ≥30/15 mmHg, respectively. Results: In this study, 215 MSA patients presented without OH, 88 had mild OH, and 141 had severe OH. The proportion of MSA-C in the severe OH subgroup was significantly higher than that in the subgroup without OH (95/46 vs. 113/102, p = 0.021). The UMSARS I score and the frequency of supine hypertension (SH) in patients with OH were significantly higher than those in patients without OH (16.22 vs. 16.89 vs. 14.60, p < 0.001; 77/64 vs. 29/59 vs. 32/183, p < 0.001). Factors related to the severity of OH included sex (OR, 0.65; p = 0.031), onset age (OR, 0.98; p = 0.029), and SH (OR, 0.21; p < 0.001). The median survival time of patients with severe OH was significantly lower than that of patients without OH (6.79 vs. 8.13 years, p = 0.001). Consistently, Cox survival analysis found that compared with patients without OH, patients with severe OH had a significantly increased risk of death (OR, 2.22; p < 0.001). Conclusion: Our large cohort study of MSA provides additional evidence for the negative impact of severe OH on survival.
Antiviral Activity of Zinc Finger Antiviral Protein (ZAP) in Different Virus Families

The CCCH-type zinc finger antiviral protein (ZAP) in humans, specifically isoforms ZAP-L and ZAP-S, is a crucial component of the cell’s intrinsic immune response. ZAP acts as a post-transcriptional RNA restriction factor, exhibiting its activity during infections caused by retroviruses and alphaviruses. Its function involves binding to CpG (cytosine-phosphate-guanine) dinucleotide sequences present in viral RNA, thereby directing it towards degradation. Since vertebrate cells have a suppressed frequency of CpG dinucleotides, ZAP is capable of distinguishing foreign genetic elements. The expression of ZAP leads to the reduction of viral replication and impedes the assembly of new virus particles. However, the specific mechanisms underlying these effects have yet to be fully understood. Several questions regarding ZAP’s mechanism of action remain unanswered, including the impact of CpG dinucleotide quantity on ZAP’s activity, whether this sequence is solely required for the binding between ZAP and viral RNA, and whether the recruitment of cofactors is dependent on cell type, among others. This review aims to integrate the findings from studies that elucidate ZAP’s antiviral role in various viral infections, discuss gaps that need to be filled through further studies, and shed light on new potential targets for therapeutic intervention.
Joint QTL Mapping and Transcriptome Sequencing Analysis Reveal Candidate Genes for Salinity Tolerance in Oryza sativa L. ssp. Japonica Seedlings

Salinity stress is one of the major abiotic stresses affecting crop growth and production. Rice is an important food crop in the world, but also a salt-sensitive crop, and the rice seedling stage is the most sensitive to salt stress, which directly affects the final yield formation. In this study, two RIL populations derived from the crosses of CD (salt-sensitive)/WD (salt-tolerant) and KY131 (salt-sensitive)/XBJZ (salt-tolerant) were used as experimental materials, and the score of salinity toxicity (SST), the relative shoot length (RSL), the relative shoot fresh weight (RSFW), and the relative shoot dry weight (RSDW) were used for evaluating the degree of tolerance under salt stress in different lines. The genetic linkage map containing 978 and 527 bin markers were constructed in two RIL populations. A total of 14 QTLs were detected on chromosomes 1, 2, 3, 4, 7, 9, 10, 11, and 12. Among them, qSST12-1, qSST12-2, and qRSL12 were co-localized in a 140-kb overlap interval on chromosome 12, which containing 16 candidate genes. Furthermore, transcriptome sequencing and qRT-PCR were analyzed in CD and WD under normal and 120 mM NaCl stress. LOC_Os12g29330, LOC_Os12g29350, LOC_Os12g29390, and LOC_Os12g29400 were significantly induced by salt stress in both CD and WD. Sequence analysis showed that LOC_Os12g29400 in the salt-sensitive parents CD and KY131 was consistent with the reference sequence (Nipponbare), whereas the salt-tolerant parents WD and XBJZ differed significantly from the reference sequence both in the promoter and exon regions. The salt-tolerant phenotype was identified by using two T3 homozygous mutant plants of LOC_Os12g29400; the results showed that the score of salinity toxicity (SST) of the mutant plants (CR-3 and CR-5) was significantly lower than that of the wild type, and the seedling survival rate (SSR) was significantly higher than that of the wild type, which indicated that LOC_Os12g29400 could negatively regulate the salinity tolerance of rice at the seedling stage. The results lay a foundation for the analysis of the molecular mechanism of rice salinity tolerance and the cultivation of new rice varieties.
Intracellular Protein Delivery: Approaches, Challenges, and Clinical Applications

Protein biologics are powerful therapeutic agents with diverse inhibitory and enzymatic functions. However, their clinical use has been limited to extracellular applications due to their inability to cross plasma membranes. Overcoming this physiological barrier would unlock the potential of protein drugs for the treatment of many intractable diseases. In this review, we highlight progress made toward achieving cytosolic delivery of recombinant proteins. We start by first considering intracellular protein delivery as a drug modality compared to existing Food and Drug Administration-approved drug modalities. Then, we summarize strategies that have been reported to achieve protein internalization. These techniques can be broadly classified into 3 categories: physical methods, direct protein engineering, and nanocarrier-mediated delivery. Finally, we highlight existing challenges for cytosolic protein delivery and offer an outlook for future advances.
Effects of sea buckthorn pomace on growth performance, serum metabolites and antioxidant indexes of growing pigs

Sea buckthorn pomace (SBP), an agro-industrial waste, containing useful nutrition compounds for animal production. This study aimed to evaluate the effect of growth performance and serum metabolisms in growing pig when consumed SBP. A total of 40 crossbred 70-day-old growing pig with initial body weight (IBW; 30 ±1.5 kg) were randomly assigned to 4 groups. The pigs were fed dietary supplementation of SBP (0.0%, 0.5, 1.5%, and 2.0 %) for 30 d. It concluded that the appropriate level of 1.5% SBP supplementation could improve pig growth performance. Serum immune and antioxidant indexes performed best in 1.5% SBP supplementation group. We suggested that the appropriate level of SBP supplementation would be 1.5% for growing pig, which could improve their growth performance, serum immune and antioxidant indexes.
Not a general, symptom-unspecific, transdiagnostic marker for functional symptoms: sensorimotor processing of head control is intact in chronic pain

Introduction Functional disorders are prevalent in all medical fields and pose a tremendous public health problem, with pain being one of the most common functional symptoms. Understanding the underlying, potentially unifying mechanism in functional (pain) disorders is instrumental in facilitating timely diagnosis, stigma reduction, and adequate treatment options. Neuroscientific models of perception suggest that functional symptoms arise due to dysregulated sensorimotor processing in the central nervous system, with brain-based predictions dominating the eventual percept. Experimental evidence for this transdiagnostic mechanism has been established in various functional symptoms. The goal of the current study was to investigate whether erroneous sensorimotor processing is an underlying transdiagnostic mechanism in chronic (functional) pain. Method A total of 13 patients with chronic (functional) pain [three patients with chronic (functional) pain disorder, F45.40, ICD-10; 10 patients with chronic pain disorder with somatic and psychological factors, F45.41, ICD-10]; and 15 healthy controls performed large combined eye-head gaze shifts toward visual targets, naturally and with increased head moment of inertia. We simultaneously measured participants' eye and head movements to assess head oscillations at the end of the gaze shift, which are an established indicator of (transdiagnostic) sensorimotor processing deficits of head control. Results Using a Bayesian analysis protocol, we found that patients with chronic (functional) pain and control participants stabilized their heads equally well (Bayes Factor 01 = 3.7, Bayes Factor exclusion = 5.23; corresponding to substantial evidence) during all sessions of the experiment. Conclusion Our results suggest that patients with chronic (functional) pain do not show measurable symptom-unspecific sensorimotor processing deficits. We discuss outcome parameter choice, organ system specificity, and selection of patient diagnoses as possible reasons for this result and recommend future avenues for research.
Computation Offloading and Resource Allocation Based on P-DQN in LEO Satellite Edge Networks

Traditional low earth orbit (LEO) satellite networks are typically independent of terrestrial networks, which develop relatively slowly due to the on-board capacity limitation. By integrating emerging mobile edge computing (MEC) with LEO satellite networks to form the business-oriented “end-edge-cloud” multi-level computing architecture, some computing-sensitive tasks can be offloaded by ground terminals to satellites, thereby satisfying more tasks in the network. How to make computation offloading and resource allocation decisions in LEO satellite edge networks, nevertheless, indeed poses challenges in tracking network dynamics and handling sophisticated actions. For the discrete-continuous hybrid action space and time-varying networks, this work aims to use the parameterized deep Q-network (P-DQN) for the joint computation offloading and resource allocation. First, the characteristics of time-varying channels are modeled, and then both communication and computation models under three different offloading decisions are constructed. Second, the constraints on task offloading decisions, on remaining available computing resources, and on the power control of LEO satellites as well as the cloud server are formulated, followed by the maximization problem of satisfied task number over the long run. Third, using the parameterized action Markov decision process (PAMDP) and P-DQN, the joint computing offloading, resource allocation, and power control are made in real time, to accommodate dynamics in LEO satellite edge networks and dispose of the discrete-continuous hybrid action space. Simulation results show that the proposed P-DQN method could approach the optimal control, and outperforms other reinforcement learning (RL) methods for merely either discrete or continuous action space, in terms of the long-term rate of satisfied tasks.
Motif Masking-based Self-Supervised Learning For Molecule Graph Representation Learning*

Molecule graph representation is an emergent technique for chemistry analysis. Integrating it with online drug sales can deeply understand the properties of drugs and realize personalized recommendations based on molecular information, which is of great significance in the intelligent analysis system and the improvement of user experience. The latest research works apply the mask-based model to represent the molecule graph and achieve great success in molecule graph representation. However, Existing mask-based molecular graph representation methods can only randomly mask single nodes, and cannot mask key functional groups in the molecular graph as a whole. This causes the mutual information of the key features of the molecule to be lost, limiting the further improvement of the performance of the molecular graph representation. To cope with this challenge, we propose a novel molecular graph representation method that uses motif vocabulary to mask critical functional groups to complement the defining mutual information of the molecular graph. First, the functional groups are discovered by motif vocabulary. Then, the discovered functional groups are masked randomly from the original graph. After, our method effectively learns a molecular graph encoder, which is enhanced by more discriminative node-node and graph-graph cross information. At last, massive experiments show that the graph representation information output by our method can be better used for downstream molecular graph classification tasks. The implementation is publicly available at https://gitee.com/wu-yasu/mmssl.git
Active Hexose-Correlated Compound Shows Direct and Indirect Effects against Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a disease characterized by the accumulation of mature CD19+CD5+CD23+ B cells in the bloodstream and in lymphoid organs. It usually affects people over 70 years of age, which limits the options for treatments. The disease is typically well-managed, but to date is still incurable. Hence, the need for novel therapeutic strategies remains. Nurse-like cells (NLCs) are major components of the microenvironment for CLL, supporting tumor cell survival, proliferation, and even drug resistance. They are of myeloid lineage, guided toward differentiating into their tumor-supportive role by the CLL cells themselves. As such, they are analogous to tumor-associated macrophages and represent a major therapeutic target. Previously, it was found that a mushroom extract, Active Hexose-Correlated Compound (AHCC), promoted the death of acute myeloid leukemia cells while preserving normal monocytes. Given these findings, it was asked whether AHCC might have a similar effect on the abnormally differentiated myeloid-lineage NLCs in CLL. CLL-patient PBMCs were treated with AHCC, and it was found that AHCC treatment showed a direct toxic effect against isolated CLL cells. In addition, it significantly reduced the number of tumor-supportive NLCs and altered their phenotype. The effects of AHCC were then tested in the Eµ-TCL1 mouse model of CLL and the MllPTD/WT Flt3ITD/WT model of AML. Results showed that AHCC not only reduced tumor load and increased survival in the CLL and AML models, but it also enhanced antitumor antibody treatment in the CLL model. These results suggest that AHCC has direct and indirect effects against CLL and that it may be of benefit when combined with existing treatments.
Deep Learning Prediction of Exonic Sequence

One of the fundamental pillars of medicine is that decision-making is based on the integration of multidimensional data and complex decision-making. Cancer presents a unique environment for medical decisions because of its diverse forms and progression. Despite advances in technology, reliable identification, characterization, and monitoring of malignancies remain a challenge. The pieces of a gene sequence can reveal details about the types of gene mutations. The exons of the prostrate genes were obtained. The DNA sequence is encoded using k-mer in a deep neural network (DNN) and bidirectional long-short-term memory (Bi-LSTM) model, and the class label is encoded using one-hot encoding. Various categorization criteria were used to evaluate the models. Our experimental findings show that the DNN model prediction achieves 96 percent testing accuracy and 99 percent training accuracy. Training accuracy for the Bi-LSTM model is 95%, and testing accuracy is 91%. Biotechnologists and doctors now have more options thanks to the quick developments in genomic technology. The development of life science technology presents new difficulties. The use of various deep learning models in bioinformatics and medicine presents a number of challenges. Furthermore, the multidisciplinary approach has resulted in the creation of improved models for prediction tasks.
Information Quality for Mobile Application Development to Assists Pilgrims: A Theoretical Model

Providing users with quality information is essential for the success of mobile application development. Hajj mobile application development is complex due to user satisfaction level, age and cultural difference, lack of interactivity, and the efficiency of the Hajj mobile application. Thus, in order to solve these problems, we intent to examine the effect of mobile information quality as the independent variables: a) content, b) contextual, and c) interaction on the effectiveness of the mobile application as the dependent variables: a) usability, and b) interactivity among user with different cultural and age range. This study identifies essential information quality dimensions which reflect to the characteristics of mobile application development in order to increase pilgrim satisfaction. There are total of 180 users selected randomly from pilgrims to validate the hypothesized model. The results show that some information quality factors are more essential than others in increasing user satisfaction and reflect the effective characteristics in mobile application development.
Industrial enzyme production in Bangladesh: current landscape, scope, and challenges

Enzymes are important biological catalysts that perform specialized functions within living organisms. Industrial enzymes are crucial in various sectors, including pharmaceuticals, the textile industry, the manufacturing of chemicals, biodiesel, the food and beverages industry, and consumer goods. Enzymes can be obtained from multiple sources, including microbes, animals, and plants. Microorganisms, especially bacteria and fungi, provide more than 50% of industrial enzymes because of their advantageous growth features, low nutritional needs, and biochemical diversity. Bangladesh's economy relies heavily on agriculture and generates biomass energy from waste such as rice husk, straw, jute sticks, and sugarcane bagasse. To reduce the environmental impact, it is vital to modify these waste materials into beneficial industrial and commercial products, like enzymes. This review article investigates the current landscape, scope, and challenges of industrial enzyme production in Bangladesh. Bangladesh has become an appealing destination for biotech firms due to variables such as yearly bio-product imports, local market consumer demand, and the availability of resources and competent people. In 2021, Bangladesh ranked as the 34th largest importer of enzymes worldwide, with an import value of $47.4 million. Bangladesh mainly imports enzymes from Turkey, Malaysia, China, Singapore, and Sri Lanka. This study identifies a critical research gap, which is the lack of a dedicated industrial enzyme production industry in Bangladesh. This gap is impeding large-scale implementation, despite ongoing research efforts. Furthermore, we suggest the establishment of a specialized industrial enzyme production sector in Bangladesh, which would benefit the environment and promote economic growth through the utilization of agro-industrial waste resources. Finally, this thorough assessment of current industrial enzyme research in Bangladesh seeks to provide researchers and stakeholders with essential information for future development. Collaboration between the government, businesses, and academics is critical to fostering growth and capitalizing on the potential of the worldwide enzyme industry. Asian J. Med. Biol. Res. 2023, 9 (4), 145-159