bluuebunny/crossref_metadata_2025 huggingface dataset:
Hidden RNA pairings counteract the “first-come, first-served” splicing principle to drive stochastic choice in
Dscam1
splice variants
Authors: Dong Haiyang , Xu Bingbing , Guo Pengjuan , Zhang Jian , Yang Xi , Li Lei , Fu Ying , Shi Jilong , Zhang Shixin , Zhu Yanda , Shi Yang , Zhou Fengyan , Bian Lina , You Wendong , Shi Feng , Yang Xiaofeng , Huang Jianhua , He Haihuai , Jin Yongfeng
Published: January 2022

Drosophila melanogaster Dscam1
encodes 38,016 isoforms via mutually exclusive splicing; however, the regulatory mechanism behind this is not fully understood. Here, we found a set of hidden RNA secondary structures that balance the stochastic choice of
Dscam1
splice variants (designated balancer RNA secondary structures). In vivo mutational analyses revealed the dual function of these balancer interactions in driving the stochastic choice of splice variants, through enhancement of the inclusion of distal exon 6s by cooperating with docking site–selector pairing to form a stronger multidomain pre-mRNA structure and through simultaneous repression of the inclusion of proximal exon 6s by antagonizing their docking site–selector pairings. Thus, we provide an elegant molecular model based on competition and cooperation between two sets of docking site–selector and balancer pairings, which counteracts the “first-come, first-served” principle. Our findings provide conceptual and mechanistic insight into the dynamics and functions of long-range RNA secondary structures.
Axial alignment is a critical regulator of knee osteoarthritis
Authors: Oláh Tamás , Reinhard Jan , Laschke Matthias W. , Goebel Lars K. H. , Walter Frédéric , Schmitt Gertrud , Speicher-Mentges Susanne , Menger Michael D. , Cucchiarini Magali , Pape Dietrich , Madry Henning
Published: January 2022

Although osteoarthritis (OA), a leading cause of disability, has been associated with joint malalignment, scientific translational evidence for this link is lacking. In a clinical case study, we provide evidence of osteochondral recovery upon unloading symptomatic isolated medial tibiofemoral knee OA associated with varus malalignment. By mapping response correlations at high resolution, we identify spatially complex degenerative changes in cartilage after overloading in a clinically relevant ovine model. We further report that unloading diminishes OA cartilage degeneration and alterations of critical parameters of the subchondral bone plate in a similar topographic fashion. Last, therapeutic unloading shifted the articular cartilage and subchondral bone phenotype to normal and restored several physiological correlations disturbed in neutral and varus OA, suggesting a protective effect on the integrity of the entire osteochondral unit. Collectively, these findings identify modifiable trajectories with considerable translational potential to reduce the burden of human OA.
Study of the Production of Poly(Hydroxybutyrate-
co
-Hydroxyhexanoate) and Poly(Hydroxybutyrate-
co
-Hydroxyvalerate-
co-
Hydroxyhexanoate) in Rhodospirillum rubrum
Authors: Cabecas Segura Paloma , Onderwater Rob , Deutschbauer Adam , Dewasme Laurent , Wattiez Ruddy , Leroy Baptiste
Published: January 2022

The use of purple bacteria, which can assimilate volatile fatty acids, for biotechnological applications has increased, since they reduce the production costs of added-value compounds such as PHA. P(HB-
co
-HHx) and P(HB-
co
-HV-
co
-HHx) have demonstrated interesting properties, notably for biomedical applications.
A Novel Method to Create Efficient Phage Cocktails via Use of Phage-Resistant Bacteria
Authors: Li Chengcheng , Shi Tongmei , Sun Yuechao , Zhang Yongyu
Published: January 2022

The rapid antiphage mutation of pathogens is a big challenge often encountered in phage therapy. Using a cocktail composed of phages with different infection strategies can better overcome this problem.
Functional Characterization of the GATA-Type Transcription Factor PaNsdD in the Filamentous Fungus Podospora anserina and Its Interplay with the Sterigmatocystin Pathway
Authors: Shen Ling , Gaslonde Thomas , Roullier Catherine , Wang Huijuan , Bodin Jennifer , Porée François-Hugues , Ruprich-Robert Gwenaël , Chapeland-Leclerc Florence
Published: January 2022

Fungal transcription factors play an essential role in coordinating multiple physiological processes. However, little is known about the functional characterization of transcription factors in the filamentous fungus
Podospora anserina
.
A Murine Commensal Protozoan Influences Host Glucose Homeostasis by Facilitating Free Choline Generation
Authors: Kou Yanbo , Meng Liyuan , Zhang Shenghan , Zheng Xingping , Liu Mengnan , Xu Shihong , Jing Qiyue , Wang Hanying , Han Jinzhi , Liu Zhuanzhuan , Wei Yanxia , Wang Yugang
Published: January 2022

Blood glucose levels are important for human health and can be influenced by gut microbes. However, its mechanism of action was previously unknown.
Glutathione Is Involved in the Reduction of Methylarsenate to Generate Antibiotic Methylarsenite in Enterobacter sp. Strain CZ-1
Authors: Huang Ke , Liu Wei , Li Yuanhe , Zeng Sha , Zhao Fang-Jie
Published: January 2022

Arsenic is a ubiquitous environmental toxin. Some microbes detoxify inorganic arsenic through biomethylation, generating relatively nontoxic pentavalent methylated arsenicals, such as methylarsenate.
Genomic Epidemiology Links Burkholderia pseudomallei from Individual Human Cases to B. pseudomallei from Targeted Environmental Sampling in Northern Australia
Authors: Webb Jessica R. , Mayo Mark , Rachlin Audrey , Woerle Celeste , Meumann Ella , Rigas Vanessa , Harrington Glenda , Kaestli Mirjam , Currie Bart J.
Published: January 2022

Each case of melioidosis results from a single event when a human is infected by the environmental bacterium
Burkholderia pseudomallei
. Darwin, in tropical northern Australia, has the highest incidences of melioidosis globally, and the Darwin Prospective Melioidosis Study (DPMS) commenced in 1989, documenting all culture-confirmed melioidosis cases.
Tumor Susceptibility Gene 101 (TSG101) Contributes to Virion Formation of Porcine Reproductive and Respiratory Syndrome Virus via Interaction with the Nucleocapsid (N) Protein along with the Early Secretory Pathway
Authors: Zhang Longxiang , Li Rui , Geng Rui , Wang Lei , Chen Xin-xin , Qiao Songlin , Zhang Gaiping
Published: January 2022

PRRSV infection results in a serious swine disease affecting pig farming in the world. However, efficient prevention and control of PRRSV is hindered by its complicated infection process.
Detection of the HIV-1 Accessory Proteins Nef and Vpu by Flow Cytometry Represents a New Tool to Study Their Functional Interplay within a Single Infected CD4
+
T Cell
Authors: Prévost Jérémie , Richard Jonathan , Gasser Romain , Medjahed Halima , Kirchhoff Frank , Hahn Beatrice H. , Kappes John C. , Ochsenbauer Christina , Duerr Ralf , Finzi Andrés
Published: January 2022

HIV-1 Nef and Vpu exert several biological functions that are important for viral immune evasion, release, and replication. Here, we developed a new method allowing simultaneous detection of these accessory proteins in their native form together with some of their cellular substrates. This allowed us to show that Vpu cannot compensate for the lack of a functional Nef, which has implications for studies that use Nef-defective viruses to study ADCC responses.
Human B Cell Responses to Dominant and Subdominant Antigens Induced by a Meningococcal Outer Membrane Vesicle Vaccine in a Phase I Trial
Authors: Rollier Christine S. , Dold Christina , Marsay Leanne , Linder Aline , Green Christopher A. , Sadarangani Manish , Norheim Gunnstein , Derrick Jeremy P. , Feavers Ian M. , Maiden Martin C. J. , Pollard Andrew J.
Published: January 2022

Neisseria meningitidis
outer membrane vesicles (OMV) are a component of the capsular group B meningococcal vaccine 4CMenB (Bexsero) and have been shown to induce 30% efficacy against gonococcal infection. They are composed of multiple antigens and are considered an interesting delivery platform for vaccines against several bacterial diseases.
Expanding the Pathogenic Potential Concept To Incorporate Fulminancy, Time, and Virulence Factors
Authors: Casadevall Arturo
Published: January 2022

The pathogenic potential (PP) concept posits that all microorganisms have some pathogenic potential that can be calculated by an equation that includes the fraction symptomatic, inoculum, and mortality fraction. The PP concept dispenses with characterizing microbes as pathogens, nonpathogens, commensals, pathobionts, etc., by providing an alternative approach to the problem of virulence that considers the contributions of both the host and the microbe.
Differential Effects of Transition Metals on Growth and Metal Uptake for Two DistinctLactobacillusSpecies
Authors: Huynh Uyen , Qiao Muxin , King John , Trinh Brittany , Valdez Juventino , Haq Marium , Zastrow Melissa L.
Published: January 2022

The gastrointestinal tract contains trillions of microorganisms, which are central to human health. Lactobacilli are considered beneficial microbiota members and are often used in probiotics, but their molecular functions, and especially those which are metal-dependent, remain poorly defined.
Myxovirus Resistance Protein A as a Marker of Viral Cause of Illness in Children Hospitalized with an Acute Infection
Authors: Piri Ruut , Yahya Mohamed , Ivaska Lauri , Toivonen Laura , Lempainen Johanna , Nuolivirta Kirsi , Tripathi Lav , Waris Matti , Peltola Ville
Published: January 2022

Due to the diagnostic uncertainty concerning the differentiation between viral and bacterial infections, children with viral infections are often treated with antibiotics, predisposing them to adverse effects and contributing to the emerging antibiotic resistance. Since currently available biomarkers only estimate the risk of bacterial infection, a biomarker for viral infection is needed in attempts of reducing antibiotic overuse.
Superoxide Initiates the Hyphal Differentiation to Microsclerotia Formation of
Macrophomina phaseolina
Authors: Liu Hsien-Hao , Huang Cheng-Chun , Lin Ying-Hong , Tseng Min-Nan , Chang Hao-Xun
Published: January 2022

Reactive oxygen species (ROS) have been proposed as the key stimulus for sclerotia development by studying fungal systems such as
Sclerotinia sclerotiorum
, and the theory has been adapted for microsclerotia development in
Verticillium dahliae
and
Nomuraea rileyi
. While many studies agreed on the association between (micro)sclerotia development and the ROS pathway, which ROS type, superoxide (

O
2
−

) or hydrogen peroxide (H
2
O
2
), plays a major role in initiating hyphal differentiation to the (micro)sclerotia formation remains controversial, and literature supporting either

O
2
−

or H
2
O
2
can be found.
Vibrio harveyi Exhibits the Growth Advantage in Stationary Phase Phenotype during Long-Term Incubation
Authors: Allen Calista , Finkel Steven E.
Published: January 2022

Vibrio harveyi
populations exist in many different niches within the ocean environment, as free-living cells, symbionts with particular squid and fish species, and parasites to other marine organisms. It is important to understand
V. harveyi
’s ability to survive and evolve within each of these niches.
Combined Host- and Pathogen-Directed Therapy for the Control of Mycobacterium abscessus Infection
Authors: Poerio Noemi , Riva Camilla , Olimpieri Tommaso , Rossi Marco , Lorè Nicola I. , De Santis Federica , Henrici De Angelis Lucia , Ciciriello Fabiana , D’Andrea Marco M. , Lucidi Vincenzina , Cirillo Daniela M. , Fraziano Maurizio
Published: January 2022

Mycobacterium abscessus
is an opportunistic pathogen intrinsically resistant to many antibiotics, frequently linked to chronic pulmonary infections, and representing a relevant cause of morbidity and mortality, especially in immunocompromised patients, such as those affected by cystic fibrosis.
M. abscessus
-caused pulmonary infection treatment is extremely difficult due to its high toxicity and long-lasting regimen with life-impairing side effects and the scarce availability of new antibiotics approved for human use. In this context, there is an urgent need for the development of an alternative therapeutic strategy that aims at improving the current management of patients affected by chronic
M. abscessus
infections.
Augmenting geological field mapping with real-time, 3-D digital outcrop scanning and modeling
Authors: Walter Callum , Faraj Fouad , Fotopoulos Georgia , Braun Alexander
Published: January 2022

Hand scanners are compact, lightweight, and capable of generating 3-D digital models. Although they do not compare to conventional methods (terrestrial laser scanning and photogrammetry) in terms of coverage, resolution, and accuracy, they offer increased mobility, speed, and real-time processing capabilities in the field. This study investigates the use of hand scanners for real-time, 3-D digital outcrop modeling to augment geological field mapping campaigns and highlights the advantages and the limitations. The utility of incorporating hand scanners as an additional tool for augmenting geological mapping is assessed based on 41 outcrop scans from the Gould Lake area, which is located 20 km north of Kingston, Ontario, Canada. The 3-D digital outcrop models gathered included two distinct metamorphic lithologies (marble and quartzofeldspathic gneiss) measuring up to 2.5 m high × 7 m long with an average surface area of 18 m2. This average scan size would take less than 10 min to capture, result in ~18 million individual points per scan, and provide a spatial resolution of ~1 cm for outcrop features. Throughout the course of the investigation, the main benefit of capturing multiple 3-D digital outcrop models was the ability to integrate this real-time, in situ geospatial, and geologic information across multiple visualization scales. This utility and retention of outcrop-scale geospatial information was shown to enhance the understanding of multi-scale geological relationships.
Supplemental Material: Tectonic burial of sedimentary rocks drives the building of juvenile crust of magmatic arc
Authors: Qin Shengkai , Zhang Zeming , al. et
Published: January 2022

Table S1: Chemical compositions of garnet from the studied pelitic migmatites (wt%). Table S2: Representative chemical compositions of main minerals from the studied pelitic migmatites (wt%). Table S3: Whole rock Sr-Nd isotopes and major element compositions of the studied pelitic migmatites, the Late Cretaceous arc magmatic rocks and Neo-Tethyan ophiolites. Table S4: Zircon U-Pb dating and trace element compositions of the pelitic migmatites and zircon standards. Table S5: Zircon Lu-Hf isotope and oxygen isotope compositions of the pelitic and mafic migmatites.
Supplemental Material: Arc-continent collision during culmination of Proto-Tethyan Ocean closure in the Central Qilian belt, NE Tibetan Plateau
Authors: Yan Zhen , al. et
Published: January 2022

Supplemental Material 1: Materials and methods. Supplemental Material 2: Supplementary Data File B. Major (wt%) and trace (ppm) element concentrations of the Dongchagou metasedimentary rock samples. Supplemental Material 3: Characteristics and U-Pb ages of zircons from the Dongchagou, Moshigou, and Qingshipo formations. Supplemental Material 4: LA-ICP-MS detrital zircon U-Pb age data for sandstone and SHRIMP zircon U-Pb age data for dolerite samples.
Acceptability of OP/Na swabbing for SARS-CoV-2: a prospective observational cohort surveillance study in Western Australian schools
Authors: Thomas Hannah M , Mullane Marianne J , Ang Sherlynn , Barrow Tina , Leahy Adele , Whelan Alexandra , Lombardi Karen , Cooper Matthew , Stevenson Paul G , Lester Leanne , Padley Andrea , Sprigg Lynn , Speers David , Merritt Adam J , Coffin Juli , Cross Donna , Gething Peter , Bowen Asha C
Published: January 2022

Objectives

When the COVID-19 pandemic was declared, Governments responded with lockdown and isolation measures to combat viral spread, including the closure of many schools. More than a year later, widespread screening for SARS-CoV-2 is critical to allow schools and other institutions to remain open. Here, we describe the acceptability of a minimally invasive COVID-19 screening protocol trialled by the Western Australian Government to mitigate the risks of and boost public confidence in schools remaining open. To minimise discomfort, and optimise recruitment and tolerability in unaccompanied children, a combined throat and nasal (OP/Na) swab was chosen over the nasopharyngeal swab commonly used, despite slightly reduced test performance.

Design, setting and participants

Trialling of OP/Na swabbing took place as part of a prospective observational cohort surveillance study in 79 schools across Western Australia. Swabs were collected from 5903 asymptomatic students and 1036 asymptomatic staff in 40 schools monthly between June and September 2020.

Outcome measures

PCR testing was performed with a two-step diagnostic and independent confirmatory PCR for any diagnostic PCR positives. Concurrent surveys, collected online through the REDCap platform, evaluated participant experiences of in-school swabbing.

Results

13 988 swabs were collected from students and staff. There were zero positive test results for SARS-CoV-2, including no false positives. Participants reported high acceptability: 71% of students reported no or minimal discomfort and most were willing to be reswabbed (4% refusal rate).

Conclusions

OP/Na swabbing is acceptable and repeatable in schoolchildren as young as 4 years old and may combat noncompliance rates by significantly increasing the acceptability of testing. This kind of minimally-invasive testing will be key to the success of ongoing, voluntary mass screening as society adjusts to a new ‘normal’ in the face of COVID-19.

Trial registration number

Australian New Zealand Clinical Trials Registry—ACTRN12620000922976.
Gut microbiota dynamics in a prospective cohort of patients with post-acute COVID-19 syndrome
Authors: Liu Qin , Mak Joyce Wing Yan , Su Qi , Yeoh Yun Kit , Lui Grace Chung-Yan , Ng Susanna So Shan , Zhang Fen , Li Amy Y L , Lu Wenqi , Hui David Shu-Cheong , Chan Paul KS , Chan Francis K L , Ng Siew C
Published: January 2022

Background

Long-term complications after COVID-19 are common, but the potential cause for persistent symptoms after viral clearance remains unclear.

Objective

To investigate whether gut microbiome composition is linked to post-acute COVID-19 syndrome (PACS), defined as at least one persistent symptom 4 weeks after clearance of the SARS-CoV-2 virus.

Methods

We conducted a prospective study of 106 patients with a spectrum of COVID-19 severity followed up from admission to 6 months and 68 non-COVID-19 controls. We analysed serial faecal microbiome of 258 samples using shotgun metagenomic sequencing, and correlated the results with persistent symptoms at 6 months.

Results

At 6 months, 76% of patients had PACS and the most common symptoms were fatigue, poor memory and hair loss. Gut microbiota composition at admission was associated with occurrence of PACS. Patients without PACS showed recovered gut microbiome profile at 6 months comparable to that of non-COVID-19 controls. Gut microbiome of patients with PACS were characterised by higher levels of Ruminococcus gnavus, Bacteroides vulgatus and lower levels of Faecalibacterium prausnitzii. Persistent respiratory symptoms were correlated with opportunistic gut pathogens, and neuropsychiatric symptoms and fatigue were correlated with nosocomial gut pathogens, including Clostridium innocuum and Actinomyces naeslundii (all p<0.05). Butyrate-producing bacteria, including Bifidobacterium pseudocatenulatum and Faecalibacterium prausnitzii showed the largest inverse correlations with PACS at 6 months.

Conclusion

These findings provided observational evidence of compositional alterations of gut microbiome in patients with long-term complications of COVID-19. Further studies should investigate whether microbiota modulation can facilitate timely recovery from post-acute COVID-19 syndrome.
Lifetime occupational exposures and chronic obstructive pulmonary disease risk in the UK Biobank cohort
Authors: De Matteis Sara , Jarvis Debbie , Darnton Lucy , Consonni Dario , Kromhout Hans , Hutchings Sally , Sadhra Steven S , Fishwick David , Vermeulen Roel , Rushton Lesley , Cullinan Paul
Published: January 2022

Background and aim

Occupational exposures are important, preventable causes of COPD. We previously found an increased risk of COPD among six occupations by analysing lifetime job histories and lung function data in the population-based UK Biobank cohort. We aimed to build on these findings and elucidate the underlying potential causal agents to focus preventive strategies.

Methods

We applied the ALOHA+job exposure matrix (JEM) based on the International Standard Classification of Occupations V.1988 codes, where exposure to 12 selected agents was rated as 0 (no exposure), 1 (low) or 2 (high). COPD was spirometrically defined as FEV1/FVC less than the lower limit of normal. We calculated semiquantitative cumulative exposure estimates for each agent by multiplying the duration of exposure and squared intensity. Prevalence ratio (PR) and 95% CI for COPD were estimated using robust Poisson regression adjusted for centre, sex, age, smoking and coexposure to JEM agents. Only associations confirmed among never-smokers and never-asthmatics were considered reliable.

Results

Out of 116 375 participants with complete job histories, 94 514 had acceptable/repeatable spirometry and smoking data and were included in the analysis. Pesticide exposure showed increased risk of COPD for ever exposure (PR=1.13, 95% CI 1.01 to 1.28) and high cumulative exposure (PR=1.32, 95% CI 1.12 to 1.56), with positive exposure–response trends (p trend=0.004), which were confirmed among never-smokers (p trend=0.005) and never-asthmatics (p trend=0.001).

Conclusion

In a large population-based study, occupational exposure to pesticides was associated with risk of COPD. Focused preventive strategies for workers exposed to pesticides can prevent the associated COPD burden.
Differences in gene expression and endophytic bacterial diversity in Atractylodes macrocephala Koidz. rhizomes from different growth years
Authors: Zhang Jianyun , Gu Xian , Zhao Yanyun , Zheng Yuguang , Wang Qian , Zheng Kaiyan , Fang Huiyong
Published: January 2022

Atractylodes macrocephala Koidz. (AMK) is widely used in traditional Chinese medicine owing to its pharmacological activity. Here, we aimed to characterize the differentially expressed genes (DEGs) of one- and three-year growth (OYG and TYG) rhizomes of AMK, combined with endophytic bacterial diversity analysis using high-throughput RNA sequencing. A total of 114 572 unigenes were annotated using six public databases. In all, 3570 DEGs revealed a clear difference, of which 936 and 2634 genes were upregulated and downregulated, respectively. The results of KEGG pathway analysis indicated that DEGs corresponding to terpenoid synthesis gene were downregulated in TYG rhizomes. In addition, 414 424 sequences corresponding to the 16S rRNA gene were divided into 1267 operational taxonomic units (OTUs). Moreover, the diversity of endophytic bacteria changed with species in the OYG (773) and TYG (1201) rhizomes at the OTU level, and Proteobacteria, Actinobacteria, and Bacteroidetes were the dominant phyla. A comparison of species differences among different growth years revealed that some species were significantly different, such as Actinomycetes, Variovorax, and Cloacibacterium. Interestingly, the decrease in the function-related metabolism of terpenoids and polyketides was correlated with the low expression of terpene synthesis genes in TYG rhizomes, as assessed using PICRUSt2. These data provide a scientific basis for elucidating the mechanisms underlying metabolite accumulation and endophytic bacterial diversity in relation to the growth years in AMK.
A new performance index for measuring the effect of single target tracking with Kalman particle filter
Authors: Lu Xinbiao , Li Fang , Tang Jing , Chai Zhuxin , Hu Mingyue
Published: January 2022

In dealing with the problems of nonlinear and non-Gaussian systems, the Kalman particle filter (KPF) algorithm has been widely used for the aerial and underwater target tracking system, which is vulnerable to environmental interference in recent years, especially in military fields. However, in most of the target tracking research, the indexes used by researchers to evaluate tracking algorithms are usually limited to the state difference or the root mean square error in the tracking process, and the overall tracking effect is only evaluated by the tracking time. These indexes cannot be evaluated for the algorithm that does not have obvious error optimization performance in the tracking process but actually improves the overall tracking effect. Therefore, this paper proposes to evaluate the tracking effect of different tracking algorithms by using the mean square error of relative points in the plane control network of engineering survey. Simulation results show that the proposed performance index combined with the tracking sampling time and the mean square error of tracking position can effectively evaluate the local and global tracking performance of different algorithms.
Nonlinear fluctuation analysis of statistical physics financial dynamics
Authors: Jia Linlu , Ke Jinchuan , Wang Jun
Published: January 2022

Based on the multi-color contact process and the oriented percolation, this paper develops a novel statistical physics financial price model with jumps to simulate and understand the price fluctuation characteristics in the real market. In this model, the interaction between investors and the dynamic changes of their investment attitudes and strategies are simulated by the complex interactions between different states of particles in the multi-color contact process. This is considered to lead to the rise and fall of the prices of financial products and affect the financial market price fluctuations. In addition, the herd behavior of investors facing sudden information outside the market also leads to dramatic price jumps. The model uses the oriented percolation combined with the Poisson process to describe those sudden fluctuations, in which the magnitude of the price jump of financial product is reconstructed by the clusters of partial interactions in the system. Therefore, the model constructs a total price process by considering both normal price fluctuations caused by the interaction of investor attitudes and sudden price jump fluctuations caused by the herd behavior. Based on the proposed model, this paper selects different parameter sets to generate the simulated return series and studies some basic descriptive statistics, stylized facts, multi-fractal property and complexity behavior of the simulated return series. To verify the rationality of the model, this paper conducts the same analysis and comparison on the return series of the real financial market. The outcomes of analysis indicate that the model proposed in this paper can reproduce the main fluctuation characteristics in the real financial market to a certain extent.
Reconstructing scalar field models of the Sharma–Mittal holographic dark energy
Authors: Upadhyay Shashikant , Dubey Vipin Chandra
Published: January 2022

In this paper, we investigate the Sharma–Mittal holographic dark energy (SMHDE) model in the context of a spatially homogeneous and isotropic flat Friedmann–Robertson–Walker (FRW) Universe by taking various values of model parameters [Formula: see text] and [Formula: see text] and the Hubble horizon is taken as the infrared cut-off. We have analyzed the deceleration parameter [Formula: see text] and the EoS parameter. According to the deceleration parameter, the Universe is in an accelerating and expanding phase, which is compatible with the observational data. The EoS parameter depicts that presently the Universe is lying in the quintessence region and at a late time it will show [Formula: see text]CDM behavior. It is also concluded by the stability analysis that SMHDE model is classically stable at present and future. To understand the dynamics of our Universe, we have established a correspondence among SMHDE and the quintessence, tachyon and K-essence scalar-field models. Our results show that the Universe is in an accelerating expansion mode described by quintessence like behavior. We go further and estimate the model parameters by using the distance modulus measurement of the recent Union 2.1 dataset of supernovae.
Experimental Studies on Geometrical Accuracy During Single-Point Incremental Forming of Inconel 625 Superalloy
Authors: Bishnoi Pawan , Chandna Pankaj
Published: January 2022

The single-point incremental forming has been globally accepted as an advanced method of sheet metal forming due to its rapid prototyping and economic benefits. The process has sensitively released the practice of using expensive dies, making it suitable for manufacturing custom-built products in tiny batches. Further, it is getting acceptance in producing parts of shabby machinery. In recent years, superalloys have become the most commonly used materials in the transportation, automotive, aeronautics and marine industries due to their fundamental and structural applications. The input parameters considered in this study are step size, feed rate and tool spindle speed. The effects of all three process parameters on the geometrical accuracy of Inconel 625 superalloy conical parts formed by the single-point incremental forming process are considered in this work. The deviations in roundness, concentricity, half-cone angle and straightness from the target values were considered as response parameters to measure the accuracy. The results showed that the part accuracy could be enhanced by using minimum step size, feed rate and maximum tool spindle speed.
First synthesis of a chlorin skeleton containing thiazole and thiophene rings and its optical properties
Authors: Nakano Takeo , Fujikawa Shigenori
Published: January 2022

A novel macrocyclic [Formula: see text]-skeleton 1 containing thiazole and thiophene rings was synthesized via MacDonald [3+1]-type condensation, and its optical properties were investigated. Two sulfur atoms were effective for the bathochromic shift of the ultraviolet-visible absorption bands in comparison with the traditional porphyrin and chlorin compounds. The characteristics of the absorption spectrum and the nucleus-independent chemical shift calculations show that the [Formula: see text]-skeleton 1 is the chlorin-type compound.
A Survey of Blockchain Data Management Systems
Authors: Wei Qian , Li Bingzhe , Chang Wanli , Jia Zhiping , Shen Zhaoyan , Shao Zili
Published: January 2022

Blockchain has been widely deployed in various fields, such as finance, education, and public services. Blockchain has decentralized mechanisms with persistency and auditability and runs as an immutable distributed ledger, where transactions are jointly performed through cryptocurrency-based consensus algorithms by worldwide distributed nodes. There have been many survey papers reviewing the blockchain technologies from different perspectives, e.g., digital currencies, consensus algorithms, and smart contracts. However, none of them have focused on the blockchain data management systems. To fill in this gap, we have conducted a comprehensive survey on the data management systems, based on three typical types of blockchain, i.e., standard blockchain, hybrid blockchain, and
DAG
(
Directed Acyclic Graph
)-based blockchain. We categorize their data management mechanisms into three layers: blockchain architecture, blockchain data structure, and blockchain storage engine, where block architecture indicates how to record transactions on a distributed ledger, blockchain data structure refers to the internal structure of each block, and blockchain storage engine specifies the storage form of data on the blockchain system. For each layer, the works advancing the state-of-the-art are discussed together with technical challenges. Furthermore, we lay out several possible future research directions for the blockchain data management systems.
Physics-Driven Page Fault Handling for Customized Deception against CPS Malware
Authors: Rrushi Julian L.
Published: January 2022

Malware crafted to attack cyber-physical systems such as the electrical power grid have a physics-centric nucleus. Cyber-physical systems malware understand physics and hence use their knowledge to guide how they initiate physical damage on a compromised industrial computer. We develop a physics-driven page fault handler in the seL4 microkernel, which, in addition to reducing the page fault rate, differentiates active physics in main memory from passive physics in the backing store. We aid the identification of active physics via a CPU scheduler that tracks the evolution of active physics over time. We exploit the concept of active physics to develop deception that is customized to attack the physics-centric nucleus of malware. We evaluated this research against a variety of malware samples and techniques, including both numerous samples from publicly available repositories and custom-made academic code, and present our findings in the article. The physics data of reference pertain to an electrical substation, with a higher focus on a power transformer and related industrial computer algorithms.
The Human Side of the Tech Industry
Authors: El-Deeb Ahmed
Published: January 2022

"Software is eating the world." wrote Marc Andreessen in his groundbreaking article in Wall Street Journal published 2014. He was pointing out that global non-tech businesses will be relying on software to deliver the core of these businesses. Fast-forward to 2021 and think about the food delivery industry, how food delivery and kitchen management have become run by software and think about the entertainment business such as Netflix and Spotify. But as the software eats the world, the question whether it can digest that amount of digital transformation and businesscritical systems without the right supply of tech talents. Shortage of tech talent is not a new topic; however, this doesn't mean that the trajectory of the problem continues to be the same when we talked about this problem 5 years ago. What's alarming is the drivers behind the talent shortage dilemma. This paper discusses key recent people-centric topics behind the tech talent dilemma.
More Is Less: Model Augmentation for Intermittent Deep Inference
Authors: Kang Chih-Kai , Mendis Hashan Roshantha , Lin Chun-Han , Chen Ming-Syan , Hsiu Pi-Cheng
Published: January 2022

Energy harvesting creates an emerging
intermittent computing
paradigm but poses new challenges for sophisticated applications such as intermittent
deep neural network
(DNN) inference. Although
model compression
has adapted DNNs to resource-constrained devices, under intermittent power, compressed models will still experience multiple power failures during a single inference. Footprint-based approaches enable hardware-accelerated intermittent DNN inference by tracking footprints, independent of model computations, to indicate accelerator progress across power cycles. However, we observe that the extra overhead required to preserve progress indicators can severely offset the computation progress accumulated by intermittent DNN inference.

This work proposes the concept of
model augmentation
to adapt DNNs to intermittent devices. Our middleware stack, JAPARI, appends extra neural network components into a given DNN, to enable the accelerator to intrinsically integrate progress indicators into the inference process, without affecting model accuracy. Their specific positions allow progress indicator preservation to be piggybacked onto output feature preservation to amortize the extra overhead, and their assigned values ensure uniquely distinguishable progress indicators for correct inference recovery upon power resumption. Evaluations on a Texas Instruments device under various DNN models, capacitor sizes, and progress preservation granularities show that JAPARI can speed up intermittent DNN inference by 3× over the state of the art, for common convolutional neural architectures that require heavy acceleration.
Efficient Realization of Decision Trees for Real-Time Inference
Authors: Chen Kuan-Hsun , Su Chiahui , Hakert Christian , Buschjäger Sebastian , Lee Chao-Lin , Lee Jenq-Kuen , Morik Katharina , Chen Jian-Jia
Published: January 2022

For timing-sensitive edge applications, the demand for efficient lightweight machine learning solutions has increased recently. Tree ensembles are among the state-of-the-art in many machine learning applications. While single decision trees are comparably small, an ensemble of trees can have a significant memory footprint leading to cache locality issues, which are crucial to performance in terms of execution time. In this work, we analyze memory-locality issues of the two most common realizations of decision trees, i.e., native and if-else trees. We highlight that both realizations demand a more careful memory layout to improve caching behavior and maximize performance. We adopt a probabilistic model of decision tree inference to find the best memory layout for each tree at the application layer. Further, we present an efficient heuristic to take architecture-dependent information into account thereby optimizing the given ensemble for a target computer architecture. Our code-generation framework, which is freely available on an open-source repository, produces optimized code sessions while preserving the structure and accuracy of the trees. With several real-world data sets, we evaluate the elapsed time of various tree realizations on server hardware as well as embedded systems for Intel and ARM processors. Our optimized memory layout achieves a reduction in execution time up to 75 % execution for server-class systems, and up to 70 % for embedded systems, respectively.
Accelerated Fire Detection and Localization at Edge
Authors: Mukherjee Arijit , Mondal Jayeeta , Dey Swarnava
Published: January 2022

Fire-related incidents continue to be reported as a leading cause of life and property destruction. Automated fire detection and localization (AFDL) systems have grown in importance with the evolution of applied robotics, especially because use of robots in disaster situations can lead to avoidance of human fatality. The importance of AFDL on resource-constrained devices has further grown, as most unmanned vehicles (drones or ground vehicles) are battery operated with limited computational capacity, the disaster situations cannot guarantee uninterrupted communication with high-end resources in the cloud, and yet faster response time is a prime necessity. Traditional computer vision–based techniques require hand-engineered features on a case-by-case basis.
Deep Learning
–based classifiers perform well for fire/no-fire classification due to the availability of large datasets for training; however, a dearth of good fire localization datasets renders the localization performance below par. We have tried to address both problems with a multi-task learned cascaded model that triggers localization workflow only if the presence of fire is detected, through a strong classifier trained on available large fire datasets. This presents only fire images to a relatively weaker localization model, reducing false positives, false negatives, and thereby improving overall AFDL accuracy. The multi-task learning (MTL) approach for end-to-end training of a stitched classifier and object localizer model on diverse datasets enabled us to build a strong fire classifier and feature extractor. It also resulted in a single unified model, capable of running on “on-board” compute infrastructure without compromising on accuracy.

To achieve the target inference rate for the AFDL deployment, we have investigated the effect of quantization and compression due to hardware acceleration on an MTL model. This article presents an approach to automate the hardware-software co-design to find the optimum parameter partitioning for a given MTL problem, especially when some parts of the model are hardware accelerated. We present combined evaluation results showing that our methodology and the corresponding AFDL model strikes a balance between the frames inferred per second and several accuracy metrics. We report fire localization accuracy in terms of mean average precision (object detection), which has not been done earlier for embedded AFDL systems.
Reduced Memory Viterbi Decoding for Hardware-accelerated Speech Recognition
Authors: Raj Pani Prithvi , Reddy Pakala Akhil , Chandrachoodan Nitin
Published: January 2022

Large Vocabulary Continuous Speech Recognition systems require Viterbi searching through a large state space to find the most probable sequence of phonemes that led to a given sound sample. This needs storing and updating of a large
Active State List (ASL)
in the
on-chip memory (OCM)
at regular intervals (called frames), which poses a major performance bottleneck for speech decoding. Most works use hash tables for OCM storage while
beam-width pruning
to restrict the ASL size. To achieve a decent accuracy and performance, a large OCM, numerous acoustic probability computations, and DRAM accesses are incurred.

We propose to use a binary search tree for ASL storage and a max heap data structure to track the worst cost state and efficiently replace it when a better state is found. With this approach, the ASL size can be reduced from over 32K to 512 with minimal impact on recognition accuracy for a 7,000-word vocabulary model. This, combined with a caching technique for acoustic scores, reduced the DRAM data accessed by 31

\( \times \)

and the acoustic probability computations by 26

\( \times \)

.

The approach has also been implemented in hardware on a Xilinx Zynq FPGA at 200 MHz using the Vivado SDS compiler. We study the tradeoffs among the amount of OCM used, word error rate, and decoding speed to show the effectiveness of the approach. The resulting implementation is capable of running faster than real time with 91% lesser block-RAMs.
Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning
Authors: Brunke Lukas , Greeff Melissa , Hall Adam W. , Yuan Zhaocong , Zhou Siqi , Panerati Jacopo , Schoellig Angela P.
Published: January 2022

The last half decade has seen a steep rise in the number of contributions on safe learning methods for real-world robotic deployments from both the control and reinforcement learning communities. This article provides a concise but holistic review of the recent advances made in using machine learning to achieve safe decision-making under uncertainties, with a focus on unifying the language and frameworks used in control theory and reinforcement learning research. It includes learning-based control approaches that safely improve performance by learning the uncertain dynamics, reinforcement learning approaches that encourage safety or robustness, and methods that can formally certify the safety of a learned control policy. As data- and learning-based robot control methods continue to gain traction, researchers must understand when and how to best leverage them in real-world scenarios where safety is imperative, such as when operating in close proximityto humans. We highlight some of the open challenges that will drive the field of robot learning in the coming years, and emphasize the need for realistic physics-based benchmarks to facilitate fair comparisons between control and reinforcement learning approaches.
Evolutionary Landscapes of Host-Virus Arms Races
Authors: Tenthorey Jeannette L. , Emerman Michael , Malik Harmit S.
Published: January 2022

Vertebrate immune systems suppress viral infection using both innate restriction factors and adaptive immunity. Viruses mutate to escape these defenses, driving hosts to counterevolve to regain fitness. This cycle recurs repeatedly, resulting in an evolutionary arms race whose outcome depends on the pace and likelihood of adaptation by host and viral genes. Although viruses evolve faster than their vertebrate hosts, their proteins are subject to numerous functional constraints that impact the probability of adaptation. These constraints are globally defined by evolutionary landscapes, which describe the fitness and adaptive potential of all possible mutations. We review deep mutational scanning experiments mapping the evolutionary landscapes of both host and viral proteins engaged in arms races. For restriction factors and some broadly neutralizing antibodies, landscapes favor the host, which may help to level the evolutionary playing field against rapidly evolving viruses. We discuss the biophysical underpinnings of these landscapes and their therapeutic implications.
Path Integrals for Nonadiabatic Dynamics: Multistate Ring Polymer Molecular Dynamics
Authors: Ananth Nandini
Published: January 2022

This review focuses on a recent class of path-integral-based methods for the simulation of nonadiabatic dynamics in the condensed phase using only classical molecular dynamics trajectories in an extended phase space. Specifically, a semiclassical mapping protocol is used to derive an exact, continuous, Cartesian variable path-integral representation for the canonical partition function of a system in which multiple electronic states are coupled to nuclear degrees of freedom. Building on this exact statistical foundation, multistate ring polymer molecular dynamics methods are developed for the approximate calculation of real-time thermal correlation functions. The remarkable promise of these multistate ring polymer methods, their successful applications, and their limitations are discussed in detail.
Laser-Induced Coulomb Explosion Imaging of Aligned Molecules and Molecular Dimers
Authors: Schouder Constant A. , Chatterley Adam S. , Pickering James D. , Stapelfeldt Henrik
Published: January 2022

We discuss how Coulomb explosion imaging (CEI), triggered by intense femtosecond laser pulses and combined with laser-induced alignment and covariance analysis of the angular distributions of the recoiling fragment ions, provides new opportunities for imaging the structures of molecules and molecular complexes. First, focusing on gas phase molecules, we show how the periodic torsional motion of halogenated biphenyl molecules can be measured in real time by timed CEI, and how CEI of one-dimensionally aligned difluoroiodobenzene molecules can uniquely identify four structural isomers. Next, focusing on molecular complexes formed inside He nano-droplets, we show that the conformations of noncovalently bound dimers or trimers, aligned in one or three dimensions, can be determined by CEI. Results presented for homodimers of CS2, OCS, and bromobenzene pave the way for femtosecond time-resolved structure imaging of molecules undergoing bimolecular interactions and ultimately chemical reactions.
Immigration and Globalization (and Deglobalization)
Authors: Leblang David , Peters Margaret E.
Published: January 2022

Immigration policy is often portrayed as a zero-sum trade-off between labor and capital or between high- and low-skilled labor. Many have attributed the rise of populist politicians and populist movements to immigrants and/or immigration policy. While immigration has distributional implications, we argue that something is clearly missing from the discussion: the fact that migrants are an engine of globalization, especially for countries in the Global South. Migration and migrant networks serve to expand economic markets, distribute information across national borders, and diffuse democratic norms and practices throughout the world, increasing trade and investment flows. We further argue that many commentators have got the causal relationship backward: Instead of immigration reducing support for globalization, we argue that trade, financial flows, and offshoring have reduced support for immigration among the elite and a vocal plurality of citizens in the Global North.