Miracle-dz/UniFAR-FTUs huggingface dataset:
Printed Stretchable Liquid Metal Electrode Arrays for In Vivo Neural Recording.

The adoption of neural interfacing into neurological diagnosis is severely hampered by the complex, costly, and error-prone manufacturing methods, requiring new fabrication processes and materials for flexible neural interfacing. Here a strategy for fabricating highly stretchable neural electrode arrays based on screen printing of liquid metal conductors onto polydimethylsiloxane substrates is presented. The screen-printed electrode arrays show a resolution of 50 µm, which is ideally applicable to neural interfaces. The integration of liquid metal-polymer conductor enables the neural electrode arrays to retain stable electrical properties and compliant mechanical performance under a significant (≈108%) strain. Taking advantage of its high biocompatibility, liquid metal electrode arrays exhibit excellent performance for neurite growth and long-term implantation. The stretchable electrode arrays can spontaneously conformally come in touch with the brain surface, and high-throughput electrocorticogram signals are recorded. Based on stretchable electrode arrays, real-time monitoring of epileptiform activities can be provided at different states of seizure. The method reported here offers a new fabrication strategy to manufacture stretchable neural electrodes, with additional potential utility in diagnostic brain-machine interfaces.
HUIL-TN & HUI-TN: Mining high utility itemsets based on pattern-growth

In recent years, high utility itemsets (HUIs) mining has been an active research topic in data mining. In this study, we propose two efficient pattern-growth based HUI mining algorithms, called High Utility Itemset based on Length and Tail-Node tree (HUIL-TN) and High Utility Itemset based on Tail-Node tree (HUI-TN). These two algorithms avoid the time-consuming candidate generation stage and the need of scanning the original dataset multiple times for exact utility values. A novel tree structure, named tail-node tree (TN-tree) is proposed as a key element of our algorithms to maintain complete utililty-information of existing itemsets of a dataset. The performance of HUIL-TN and HUI-TN was evaluated against state-of-the-art reference methods on various datasets. Experimental results showed that our algorithms exceed or close to the best performance on all datasets in terms of running time, while other algorithms can only excel in certain types of dataset. Scalability tests were also performed and our algorithms obtained the flattest curves among all competitors.
Phenolic compounds, flavonoids and antioxidant activity in different cocoa samples from organic and conventional cultivation

Purpose – Due to the importance attributed to the phenolic compounds present in cocoa samples for their beneficial effects on health, the purpose of this paper was to analyze four samples of organically and conventionally cultivated cocoa from the south area of Bahia for their composition of phenolics, flavonoids and their antioxidant activity.Design/methodology/approach – Non‐fermented beans, fermented beans, roasted nibs and cocoa liquor were analyzed using spectrophotometry.Findings – In general, the samples that contained a higher level of phenolics and flavonoids were the roasted nibs and the non‐fermented samples in both cultivation systems. The fermented beans and the liquor contained a lower level.Practical implications – The relationship between the concentration of total phenols and the capacity to “mop up” free radicals from the cocoa extracts appears to be highly significant. The extracts with a higher concentration of phenols also show higher antioxidant activity (non‐fermented beans extracts.
ACE: the Advanced Cohort Engine for searching longitudinal patient records

Abstract Objective To propose a paradigm for a scalable time-aware clinical data search, and to describe the design, implementation and use of a search engine realizing this paradigm. Materials and Methods The Advanced Cohort Engine (ACE) uses a temporal query language and in-memory datastore of patient objects to provide a fast, scalable, and expressive time-aware search. ACE accepts data in the Observational Medicine Outcomes Partnership Common Data Model, and is configurable to balance performance with compute cost. ACE’s temporal query language supports automatic query expansion using clinical knowledge graphs. The ACE API can be used with R, Python, Java, HTTP, and a Web UI. Results ACE offers an expressive query language for complex temporal search across many clinical data types with multiple output options. ACE enables electronic phenotyping and cohort-building with subsecond response times in searching the data of millions of patients for a variety of use cases. Discussion ACE enables fast, time-aware search using a patient object-centric datastore, thereby overcoming many technical and design shortcomings of relational algebra-based querying. Integrating electronic phenotype development with cohort-building enables a variety of high-value uses for a learning health system. Tradeoffs include the need to learn a new query language and the technical setup burden. Conclusion ACE is a tool that combines a unique query language for time-aware search of longitudinal patient records with a patient object datastore for rapid electronic phenotyping, cohort extraction, and exploratory data analyses.
Improving waste activated sludge dewaterability with sodium periodate pre‐oxidation on extracellular polymeric substances

The efficiency of sludge dewatering is affected by the structure and composition of hydrated extracellular polymeric substances (EPS). Degrading EPS can improve the sludge dewatering performance. As an oxidizing agent, sodium periodate (NaIO4) has ability to oxidize organics, which is expected to decompose the protein and polysaccharide in EPS and improve the efficiency of sludge dewaterability. This study adopted NaIO4, for the first time, as an advanced oxidation agent to regulate EPS of waste activated sludge and was combined with anionic polyacrylamide (APAM) as a flocculant to subsequently enhance sludge dewatering. Response surface methodology (RSM) was used to determine the optimal conditions of pH, NaIO4, and APAM. The results showed that the composite conditioner's specific resistance of filtration (SRF) and the water content of the vacuum‐filtered cake (Wc) were highly enhanced compared with those of the raw sludge (RS) under pH 6.5, a NaIO4 concentration of 50 mg/g dry solids (DS), and an APAM concentration of 5 mg/g DS. Owing to the pre‐oxidation achieved by NaIO4 under a mildly acid environment, sludge flocs were broken. Subsequently, chemical coagulation (APAM) agglomerated the smaller particles into larger flocs of sludge by adsorption and bridging, thus improving sludge dewaterability.
Q-Learning for Feedback Nash Strategy of Finite-Horizon Nonzero-Sum Difference Games

In this article, we study the feedback Nash strategy of the model-free nonzero-sum difference game. The main contribution is to present the <inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula>-learning algorithm for the linear quadratic game without prior knowledge of the system model. It is noted that the studied game is in finite horizon which is novel to the learning algorithms in the literature which are mostly for the infinite-horizon Nash strategy. The key is to characterize the <inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula>-factors in terms of the arbitrary control input and state information. A numerical example is given to verify the effectiveness of the proposed algorithm.
A Multiscale Interactive Recurrent Network for Time-Series Forecasting

Time-series forecasting is a key component in the automation and optimization of intelligent applications. It is not a trivial task, as there are various short-term and/or long-term temporal dependencies. Multiscale modeling has been considered as a promising strategy to solve this problem. However, the existing multiscale models either apply an implicit way to model the temporal dependencies or ignore the interrelationships between multiscale subseries. In this article, we propose a multiscale interactive recurrent network (MiRNN) to jointly capture multiscale patterns. MiRNN employs a deep wavelet decomposition network to decompose the raw time series into multiscale subseries. MiRNN introduces three key strategies (truncation, initialization, and message passing) to model the inherent interrelationships between multiscale subseries, as well as a dual-stage attention mechanism to capture multiscale temporal dependencies. Experiments on four real-world datasets demonstrate that our model achieves promising performance compared with the state-of-the-art methods.
DAMAD: Database, Attack, and Model Agnostic Adversarial Perturbation Detector

Adversarial perturbations have demonstrated the vulnerabilities of deep learning algorithms to adversarial attacks. Existing adversary detection algorithms attempt to detect the singularities; however, they are in general, loss-function, database, or model dependent. To mitigate this limitation, we propose DAMAD—a generalized perturbation detection algorithm which is agnostic to model architecture, training data set, and loss function used during training. The proposed adversarial perturbation detection algorithm is based on the fusion of autoencoder embedding and statistical texture features extracted from convolutional neural networks. The performance of DAMAD is evaluated on the challenging scenarios of cross-database, cross-attack, and cross-architecture training and testing along with traditional evaluation of testing on the same database with known attack and model. Comparison with state-of-the-art perturbation detection algorithms showcase the effectiveness of the proposed algorithm on six databases: ImageNet, CIFAR-10, Multi-PIE, MEDS, point and shoot challenge (PaSC), and MNIST. Performance evaluation with nearly a quarter of a million adversarial and original images and comparison with recent algorithms show the effectiveness of the proposed algorithm.
Interface Response Functions for Amorphous and Crystalline Si and the Implications for Explosive Crystallization

Interface response functions (IRFs) for amorphous and crystalline forms of Si have been determined for several empirical atomic-scale models using Molecular Dynamics and compared to available experimental results fitted to a Wilson-Frenkel equation form. Stillinger–Weber (SW), the environment-dependent intermolecular potential (EDIP), and a version of the modified embedded atom method (MEAM) models were found to produce unacceptable representations of the IRFs of both solid phases; they were either unable to predict the amorphous melting point and/or the maximum solidification velocity. The best of these models was judged to be the SW potential, known to produce a very accurate IRF for crystalline silicon. Increasing the strength of the three-body term by up to 25% above that of the original SW potential improves the prediction of the melting characteristics of the amorphous phase. Above this limit, liquid phase properties are impaired. The resultant IRFs provide an important backdrop to understand the kinetics of explosive crystallization (EC) processes, as we shall show in comparison to recent experimental data on the EC of amorphous Ge. [A. Chojnacka and M.O. Thompson, in Growth, Evolution and Properties of Surfaces, Thin Films and Self-Organized Structures, edited by S.C. Moss, D.B. Poker, D. Ila, (Mat. Res. Soc. Symp. Proc. 648, Warrendale, PA 2001) p. P11.12. 1–8]. We also provide evidence that homogeneous melting within the bulk of the amorphous material competes with heterogeneous melting at the planar amorphous/liquid interface.
Ozone Therapy in Cancer Treatment: State of the Art

Erhlich Ascitic Tumor and Sarcoma 37 were implanted in mice and afterward the animals were treated with ozone (rectally). A significant decrease in the number of metastasis was obtained. In another study, ozone was applied intraperitoneally, before Lewis' lung carcinoma inoculation. A delayed effect in the tumor development kinetics and in the increase rate of tumor volume in the ozone groups was observed. With regard to the clinical trial, patients with prostatic cancer were treated with cobalt-60 therapy and ozone (rectally), decreasing the presence of side effects (due to radiation treatment) and the prostatic specific antigen figures. However, further investigations are necessary to be performed, in order to be considered the ozone therapy as complementary therapy for cancer.
Structure-function analysis of fission yeast cleavage and polyadenylation factor (CPF) subunit Ppn1 and its interactions with Dis2 and Swd22

Fission yeast Cleavage and Polyadenylation Factor (CPF), a 13-subunit complex, executes the cotranscriptional 3’ processing of RNA polymerase II (Pol2) transcripts that precedes transcription termination. The three-subunit DPS sub-complex of CPF, consisting of a PP1-type phosphoprotein phosphatase Dis2, a WD-repeat protein Swd22, and a putative phosphatase regulatory factor Ppn1, associates with the CPF core to form the holo-CPF assembly. Here we probed the functional, physical, and genetic interactions of DPS by focusing on the Ppn1 subunit, which mediates association of DPS with the core. Transcriptional profiling by RNA-seq defined limited but highly concordant sets of protein-coding genes that were dysregulated in ppn1Δ, swd22Δ and dis2Δ cells, which included the DPSΔ down-regulated phosphate homeostasis genes pho1 and pho84 that are controlled by lncRNA-mediated transcriptional interference. Essential and inessential modules of the 710-aa Ppn1 protein were defined by testing the effects of Ppn1 truncations in multiple genetic backgrounds in which Ppn1 is required for growth. An N-terminal 172-aa disordered region was dispensable and its deletion alleviated hypomorphic phenotypes caused by deleting C-terminal aa 640–710. A TFIIS-like domain (aa 173–330) was not required for viability but was important for Ppn1 activity in phosphate homeostasis. Distinct sites within Ppn1 for binding to Dis2 (spanning Ppn1 aa 506 to 532) and Swd22 (from Ppn1 aa 533 to 578) were demarcated by yeast two-hybrid assays. Dis2 interaction-defective missense mutants of full-length Ppn1 (that retained Swd22 interaction) were employed to show that binding to Dis2 (or its paralog Sds21) was necessary for Ppn1 biological activity. Ppn1 function was severely compromised by missense mutations that selectively affected its binding to Swd22.
Improving Acetic Acid and Furfural Resistance of Xylose-Fermenting Saccharomyces cerevisiae Strains by Regulating Novel Transcription Factors Revealed via Comparative Transcriptomic Analysis

Inhibitor tolerance is essential for S. cerevisiae when fermenting lignocellulosic hydrolysate with various inhibitors, including weak acids, furans, and phenols. The details regarding how xylose-fermenting S. cerevisiae strains respond to multiple inhibitors during fermenting mixed glucose and xylose are still unknown. ABSTRACT Acetic acid and furfural are the two prevalent inhibitors coexisting with glucose and xylose in lignocellulosic hydrolysate. The transcriptional regulations of Saccharomyces cerevisiae in response to acetic acid (Aa), furfural (Fur), and the mixture of acetic acid and furfural (Aa_Fur) were revealed during mixed glucose and xylose fermentation. Carbohydrate metabolism pathways were significantly enriched in response to Aa, while pathways of xenobiotic biodegradation and metabolism were significantly enriched in response to Fur. In addition to these pathways, other pathways were activated in response to Aa_Fur, i.e., cofactor and vitamin metabolism and lipid metabolism. Overexpression of Haa1p or Tye7p improved xylose consumption rates by nearly 50%, while the ethanol yield was enhanced by nearly 8% under acetic acid and furfural stress conditions. Co-overexpression of Haa1p and Tye7p resulted in a 59% increase in xylose consumption rate and a 12% increase in ethanol yield, revealing the beneficial effects of Haa1p and Tye7p on improving the tolerance of yeast to mixed acetic acid and furfural. IMPORTANCE Inhibitor tolerance is essential for S. cerevisiae when fermenting lignocellulosic hydrolysate with various inhibitors, including weak acids, furans, and phenols. The details regarding how xylose-fermenting S. cerevisiae strains respond to multiple inhibitors during fermenting mixed glucose and xylose are still unknown. This study revealed the transcriptional regulation mechanism of an industrial xylose-fermenting S. cerevisiae strain in response to acetic acid and furfural. The transcription factor Haa1p was found to be involved in both acetic acid and furfural tolerance. In addition to Haa1p, four other transcription factors, Hap4p, Yox1p, Tye7p, and Mga1p, were identified as able to improve the resistance of yeast to these two inhibitors. This study underscores the feasibility of uncovering effective transcription factors for constructing robust strains for lignocellulosic bioethanol production.
Automated Design of Multipass Heuristics for Resource-Constrained Job Scheduling With Self-Competitive Genetic Programming

Resource constraint job scheduling is an important combinatorial optimization problem with many practical applications. This problem aims at determining a schedule for executing jobs on machines satisfying several constraints (e.g., precedence and resource constraints) given a shared central resource while minimizing the tardiness of the jobs. Due to the complexity of the problem, several exact, heuristic, and hybrid methods have been attempted. Despite their success, scalability is still a major issue of the existing methods. In this study, we develop a new genetic programming algorithm for resource constraint job scheduling to overcome or alleviate the scalability issue. The goal of the proposed algorithm is to evolve effective and efficient multipass heuristics by a surrogate-assisted learning mechanism and self-competitive genetic operations. The experiments show that the evolved multipass heuristics are very effective when tested with a large dataset. Moreover, the algorithm scales very well as excellent solutions are found for even the largest problem instances, outperforming existing metaheuristic and hybrid methods.
Prevalence and distribution of multilocus sequence types of Staphylococcus aureus isolated from bulk tank milk and cows with mastitis in Pennsylvania

A total of 163 S. aureus isolates; 113 from mastitic milk (MM) and 50 from bulk tank milk (BTM) (2008, 2013–2015) submitted for bacteriologic analysis at the Penn State Animal Diagnostic Laboratory were examined for their phenotypic and genotypic characteristics. Multi-locus sequence typing (MLST) analysis identified 16 unique sequence types (STs) which belonged to eight clonal complexes (CCs). Majority of the isolates were variants of CC97 (68.7%) and CC151 (25.1%). CC97 comprised of seven STs, of which two were new STs (ST3273, ST3274), while CC151 comprised of three STs of which ST3272 was identified for the first time. Several farms had more than one ST type that were either members of the same clonal complex or unrelated STs. On one farm, six different STs of both categories were seen over the years within the farm. It was observed that ST352 and ST151 were the two main clonal populations in cattle not only in Pennsylvania but also globally. Most isolates were susceptible to all the antibiotics evaluated. 6.7% of isolates showed resistance to vancomycin and penicillin. Two isolates of ST398 showed multidrug resistance (>3 antibiotics) against clindamycin, erythromycin, tetracycline, and penicillin. It was noted that 59 of 163 (36.2%) isolates encoded for enterotoxigenic genes. Enterotoxin genes seg/sei accounted for ~85% of enterotoxin positive isolates. Toxic shock syndrome gene tsst-1 alone was positive in two isolates (ST352, ST 2187). 97.5% of CC151 isolates were enterotoxin seg/sei positive. Most isolates were positive for lukED (95%) and lukAB (96.3%) leukotoxin genes. Bovine specific bi-component leucocidin lukMF’ was present in 54% of isolates. A prominent observation of this study was the explicit association of lukMF’ with lineages ST151 and ST352. In conclusion, the findings of the study, suggest that small number of S. aureus STs types (ST352, ST2187, ST3028, and ST151) are associated with majority of cases of bovine mastitis in Pennsylvania dairy farms. It was observed that one ST of S. aureus predominated in the herd and this ST can coexist with several other ST types of S. aureus strains. When STs were interpreted along with virulence, leucocidin genes and antimicrobial resistance, ST-variants allowed better interpretation of the S. aureus molecular epidemiologic findings specifically for tracing recurrence or persistence of infections in cow over time, among cows in the herd, and between herds in Pennsylvania.
Seroprevalence of Antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 Among Healthcare Workers in Kenya

Background Few studies have assessed the seroprevalence of antibodies against SARS-CoV-2 among Health Care Workers (HCWs) in Africa. We report findings from a survey among HCWs in three counties in Kenya. Methods We recruited 684 HCWs from Kilifi (rural), Busia (rural) and Nairobi (urban) counties. The serosurvey was conducted between 30th July 2020 and 4th December 2020. We tested for IgG antibodies to SARS-CoV-2 spike protein using ELISA. Assay sensitivity and specificity were 93% (95% CI 88-96%) and 99% (95% CI 98-99.5%), respectively. We adjusted prevalence estimates using Bayesian modeling to account for assay performance. Results Crude overall seroprevalence was 19.7% (135/684). After adjustment for assay performance seroprevalence was 20.8% (95% CI 17.5-24.4%). Seroprevalence varied significantly (p<0.001) by site: 43.8% (CI 35.8-52.2%) in Nairobi, 12.6% (CI 8.8-17.1%) in Busia and 11.5% (CI 7.2-17.6%) in Kilifi. In a multivariable model controlling for age, sex and site, professional cadre was not associated with differences in seroprevalence. Conclusion These initial data demonstrate a high seroprevalence of antibodies to SARS-CoV-2 among HCWs in Kenya. There was significant variation in seroprevalence by region, but not by cadre.
Diurnal Variation in SARS-CoV-2 PCR Test Results: Test Accuracy May Vary by Time of Day

False negative tests for SARS-CoV-2 are common and have important public health and medical implications. We tested the hypothesis of diurnal variation in viral shedding by assessing the proportion of positive versus negative SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) tests and cycle time (Ct) values among positive samples by the time of day. Among 86,342 clinical tests performed among symptomatic and asymptomatic patients in a regional health care network in the southeastern United States from March to August 2020, we found evidence for diurnal variation in the proportion of positive SARS-CoV-2 tests, with a peak around 1400 h and 1.7-fold variation over the day after adjustment for age, sex, race, testing location, month, and day of week and lower Ct values during the day for positive samples. These findings have important implications for public health testing and vaccination strategies.