Miracle-dz/UniFAR-FTUs huggingface dataset:
The Sequent Calculus of Skew Monoidal Categories

Szlach\'anyi's skew monoidal categories are a well-motivated variation of monoidal categories in which the unitors and associator are not required to be natural isomorphisms, but merely natural transformations in a particular direction. We present a sequent calculus for skew monoidal categories, building on the recent formulation by one of the authors of a sequent calculus for the Tamari order (skew semigroup categories). In this calculus, antecedents consist of a stoup (an optional formula) followed by a context, and the connectives behave like in the standard monoidal sequent calculus except that the left rules may only be applied in stoup position. We prove that this calculus is sound and complete with respect to existence of maps in the free skew monoidal category, and moreover that it captures equality of maps once a suitable equivalence relation is imposed on derivations. We then identify a subsystem of focused derivations and establish that it contains exactly one canonical representative from each equivalence class. This coherence theorem leads directly to simple procedures for deciding equality of maps in the free skew monoidal category and for enumerating any homset without duplicates. Finally, and in the spirit of Lambek's work, we describe the close connection between this proof-theoretic analysis and Bourke and Lack's recent characterization of skew monoidal categories as left representable skew multicategories. We have formalized this development in the dependently typed programming language Agda.
Centromere Plasticity With Evolutionary Conservation and Divergence Uncovered by Wheat 10+ Genomes

Abstract Centromeres (CEN) are the chromosomal regions that play a crucial role in maintaining genomic stability. The underlying highly repetitive DNA sequences can evolve quickly in most eukaryotes, and promote karyotype evolution. Despite their variability, it is not fully understood how these widely variable sequences ensure the homeostasis of centromere function. In this study, we investigated the genetics and epigenetics of CEN in a population of wheat lines from global breeding programs. We captured a high degree of sequences, positioning, and epigenetic variations in the large and complex wheat CEN. We found that most CENH3-associated repeats are Cereba element of retrotransposons and exhibit phylogenetic homogenization across different wheat lines, but the less-associated repeat sequences diverge on their own way in each wheat line, implying specific mechanisms for selecting certain repeat types as functional core CEN. Furthermore, we observed that CENH3 nucleosome structures display looser wrapping of DNA termini on complex centromeric repeats, including the repositioned CEN. We also found that strict CENH3 nucleosome positioning and intrinsic DNA features play a role in determining centromere identity among different lines. Specific non-B form DNAs were substantially associated with CENH3 nucleosomes for the repositioned centromeres. These findings suggest that multiple mechanisms were involved in the adaptation of CENH3 nucleosomes that can stabilize CEN. Ultimately, we proposed a remarkable epigenetic plasticity of centromere chromatin within the diverse genomic context, and the high robustness is crucial for maintaining centromere function and genome stability in wheat 10+ lines as a result of past breeding selections.
Next generation anticoagulants: a spotlight on the potential role of activated factors XII and XI

Arterial and venous thrombosis are the leading causes of morbidity and mortality in the developed world. Anticoagulation remains the mainstay care for treatment or prevention of thrombosis. The past decade has produced direct oral anticoagulants (DOACs) which selectively inhibit activated Factor X(a) or thrombin. However, hitherto, all anticoagulants available increase bleeding risk. The ‘holy grail’ of anticoagulant therapy is to limit bleeding whilst achieving optimal anticoagulant efficacy. In this context, efforts have turned to the development of alternative antithrombotic approaches that carry reduced bleeding risk.
Perioperative Stroke and Thirty-Day Hospital Readmission After Cardiac Surgeries: State Inpatient Database Study

Background Readmission rates are an important metric for evaluating healthcare quality. Stroke is a major complication following cardiac surgery. Our study aimed to evaluate the frequency and predictors of 30-day unplanned hospital readmission after cardiac surgeries and to evaluate the impact of perioperative stroke on readmission. Methods Surgical discharge records spanning the years of 2008 through 2011 were analyzed utilizing California State Inpatient Database. International Classification of Diseases, ninth revision-Clinical Modification (ICD-9-CM) codes and Clinical Classification Software (CCS) codes were used to identify surgeries and variables of interest. Surgical records were then followed up for 30 days through linking admission records. Perioperative stroke was defined as brain infarction of ischemic or hemorrhagic etiology that occurred during or within 30 days after surgery. Results Baseline characteristics associated with increased readmission rates were female gender, age above 65, non-white race, lower income, and increased number of comorbidities. Among 199,617 hospitalizations for cardiac surgeries, 1,817 (0.91%) patients developed perioperative stroke. The rate of readmission in perioperative stroke patients was 21.89%. They had a longer length of hospital stay and their discharge was vastly non-routine (84%). Our univariate analysis yielded significant association between stroke and readmission rates (odds ratio: 1.82, 95% confidence interval: 1.63 - 2.04). This association failed to remain significant upon controlling for other variables in our multivariate analysis. Conclusion Baseline patient characteristics and perioperative complications are significant predictors of readmission. More than one in five patients who develop a stroke after cardiac surgery are readmitted to the hospital within 30 days of discharge.
Characterizing the dynamics of BCR repertoire from repeated influenza vaccination

ABSTRACT Yearly epidemics of seasonal inﬂuenza cause an enormous disease burden around the globe. An understanding of the rules behind the immune response with repeated vaccination still presents a significant challenge, which would be helpful for optimizing the vaccination strategy. In this study, 34 healthy volunteers with 16 vaccinated were recruited, and the dynamics of the BCR repertoire for consecutive vaccinations in two seasons were tracked. In terms of diversity, length, network, V and J gene segments usage, somatic hypermutation (SHM) rate and isotype, it was found that the overall changes were stronger in the acute phase of the first vaccination than the second vaccination. However, the V gene segments of IGHV4-39, IGHV3-9, IGHV3-7 and IGHV1-69 were amplified in the acute phase of the first vaccination, with IGHV3-7 dominant. On the other hand, for the second vaccination, the changes were dominated by IGHV1-69, with potential for coding broad neutralizing antibody. Additional analysis indicates that the application of V gene segment for IGHV3-7 in the acute phase of the first vaccination was due to the elevated usage of isotypes IgM and IgG3. While for IGHV1-69 in the second vaccination, it was contributed by isotypes IgG1 and IgG2. Finally, 41 public BCR clusters were identified in the vaccine group, with both IGHV3-7 and IGHV1-69 were involved and representative complementarity determining region 3 (CDR3) motifs were characterized. This study provides insights into the immune response dynamics following repeated influenza vaccination in humans and can inform universal vaccine design and vaccine strategies in the future.
Computational Social Psychology.

Social psychologists attempt to explain how we interact by appealing to basic principles of how we think. To make good on this ambition, they are increasingly relying on an interconnected set of formal tools that model inference, attribution, value-guided decision making, and multi-agent interactions. By reviewing progress in each of these areas and highlighting the connections between them, we can better appreciate the structure of social thought and behavior, while also coming to understand when, why, and how formal tools can be useful for social psychologists. Expected final online publication date for the Annual Review of Psychology, Volume 75 is January 2024. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
An E cient Approximation Algorithm for Minimizing Makespanon Uniformly Related Machines

We give a new eecient approximation algorithm for scheduling precedence constrained jobs on machines with diierent speeds. The problem is as follows. We are given n jobs to be scheduled on a set of m machines. Jobs have processing times and machines have speeds. It takes p j =s i units of time for machine i with speed s i to process job j with processing requirement p j. Precedence constraints between jobs are given in the form of a partial order. If j k, processing of k cannot start until j's execution is completed. The objective is to nd a non-preemptive schedule to minimize C max = max j C j , conventionally called the makespan of the schedule, where C j is the completion time of job j. Recently Chudak and Shmoys 2] gave an algorithm with an approximation ratio of O(log m) signiicantly improving the earlier ratio of O(p m) due to Jaae 6]. Their algorithm is based on solving a linear programming relaxation of the problem. Building on some of their ideas, we present a combinatorial algorithm that achieves a similar approximation ratio but runs in O(n 3) time. In the process we also obtain a constant factor approximation algorithm for the special case of precedence constraints induced by a collection of chains. Our algorithm is based on a new lower bound which we believe is of independent interest. Using a result of Shmoys, Wein, and Williamson 10] our algorithm can be extended to obtain an O(log m) approximation ratio even if jobs have release dates.
PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences

Given the emerging global threat of antimicrobial resistance, new methods for next-generation antimicrobial design are urgently needed. We report a peptide generation framework PepCVAE, based on a semi-supervised variational autoencoder (VAE) model, for designing novel antimicrobial peptide (AMP) sequences. Our model learns a rich latent space of the biological peptide context by taking advantage of abundant, unlabeled peptide sequences. The model further learns a disentangled antimicrobial attribute space by using the feedback from a jointly trained AMP classifier that uses limited labeled instances. The disentangled representation allows for controllable generation of AMPs. Extensive analysis of the PepCVAE-generated sequences reveals superior performance of our model in comparison to a plain VAE, as PepCVAE generates novel AMP sequences with higher long-range diversity, while being closer to the training distribution of biological peptides. These features are highly desired in next-generation antimicrobial design.
The σB alternative sigma factor circuit modulates noise to generate different types of pulsing dynamics

Single-cell approaches are revealing a high degree of heterogeneity, or noise, in gene expression in isogenic bacteria. How gene circuits modulate this noise in gene expression to generate robust output dynamics is unclear. Here we use the Bacillus subtilis alternative sigma factor σB as a model system for understanding the role of noise in generating circuit output dynamics. σB controls the general stress response in B. subtilis and is activated by a range of energy and environmental stresses. Recent single-cell studies have revealed that the circuit can generate two distinct outputs, stochastic pulsing and a single pulse response, but the conditions under which each response is generated are under debate. We implement a stochastic mathematical model of the σB circuit to investigate this and find that the system’s core circuit can generate both response types. This is despite one response (stochastic pulsing) being stochastic in nature, and the other (single response pulse) being deterministic. We demonstrate that the main determinant for whichever response is generated is the degree with which the input pathway activates the core circuit, although the noise properties of the input pathway also biases the system towards one or the other type of output. Thus, our work shows how stochastic modelling can reveal the mechanisms behind non-intuitive gene circuit output dynamics.
Liquid biopsies for detection, surveillance, and prognosis of urothelial cancer: a future standard?

ABSTRACT Introduction Liquid biopsies are used for the detection of tumor-specific elements in body fluid. Their application in prognosis and diagnosis of muscle/non-muscle invasive bladder cancer (MIBC/NMIBC) or upper tract urothelial cancer (UTUC) remains poorly known and rarely mentioned in clinical guidelines. Areas covered Herein, we provide an overview of current data regarding the use of liquid biopsies in urothelial tumors. Expert opinion Studies that were included analyzed liquid biopsies using the detection of circulating tumor cells (CTCs), deoxyribonucleic acid (DNA), ribonucleic acid (RNA), exosomes, or metabolomics. The sensitivity of blood CTC detection in patients with localized cancer was 35% and raised to 50% in patients with metastatic cancer. In NMIBC patients, blood CTC was associated with poor prognosis, whereas discrepancies were seen in MIBC patients. Circulating plasma DNA presented a superior sensitivity to urine and was a good indicator for diagnosis, follow-up, and oncological outcome. In urine, specific bladder cancer (BC) microRNA had an overall sensitivity of 85% and a specificity of 86% in the diagnosis of urothelial cancer. These results are in favor of the use of liquid biopsies as biomarkers for in urothelial cancer management.
Hydraulic Variable Valve Actuation on a Single Cylinder Engine

The combustion characteristics in an engine cylinder can greatly change over a range of speeds and loads. However, conventional engines fix the timing and amount of intake and exhaust, which can lead to higher emissions, wasted fuel, and lower power output. This thesis studies the application of a hydraulics based variable valve actuation system to change the valves’ lift and timing on a single cylinder spark ignition engine. In addition to controlling the valve actuation, a hydraulics based design has the advantage of protecting against engine failure in cases of electrical power loss, reverting the system to behave as a conventional camshaft valve train. The research extends the previous iterations of the hydraulics design to prevent leakage, retain pressure, and reliably open and close the engine valves. A hydraulic cylinder is used to replace the conventional cam where pressurized fluid opens, and spring force closes, the engine valve. The pressurized fluid is supplied to, or removed from, the cylinder using rotary spool valves coupled to the engine crankshaft. Additionally, the system is modelled in Simulink to determine the effect of system pressure, flow area, and spring rate on the resulting valve profile. After modelling the system’s performance for achieving variable lift and timing, the system was designed, manufactured, and tested on a single cylinder engine with the aid of a dynamometer. Experimental results for valve lift showed good agreement with the simulation models. Majority of the tests were performed using manual control, followed by experiments with active control of the system pressure to reach a desired valve lift. The lift controller is able to achieve the desired valve actuation in under 2 seconds with active pressure feedback. Lastly, the ability of the hydraulic variable valve system as a viable alternative is shown by achieving combustion at 1500 RPM engine idle speed.
Near-optimal practical convergent method for interference alignment in MIMO interference channels

A practical distributed Gauss–Newton method for the near-optimal computation of interference alignment solutions is proposed, based on the block-wise structure of Jacobian matrix of the residual interference function. Also, a simple practical matrix inverse computation algorithm to solve the rank-deficient problem due to the interference sparse matrix is adopted. This proposal achieves convergent performance comparable to centralised Gauss–Newton method, with the major advantage of being practically implemented in a distributed manner.
The Impact of the Mediterranean Diet and Lifestyle Intervention on Lipoprotein Subclass Profiles among Metabolic Syndrome Patients: Findings of a Randomized Controlled Trial

Background: Metabolic syndrome (MetS) is associated with alterations of lipoprotein structure and function that can be characterized with advanced lipoprotein testing (ADLT). The effect of Mediterranean diet (MedDiet) and of body weight loss on the lipoprotein subclass profile has been scarcely studied. Within the PREDIMED-Plus randomized controlled trial, a sub-study conducted in one of its recruiting centers aimed to evaluate the effects on lipoproteins properties assessed by ADLT of an intensive weight loss program based on an energy-reduced MedDiet (er-MedDiet) and physical activity (PA) promotion (intervention group) compared with energy-unrestricted MedDiet recommendations (control group) on lipoprotein subclasses. Methods: 202 patients with MetS (n=107, Intervention; n=95, Control) were included in this study. Conventional lipid profile and ADLTs were performed at baseline, 6 months and one year. Linear mixed models were used to assess the effects of intervention on lipoprotein profiles. Results: The er-MedDiet+PA led to a significant decrease of body mass index by 1.5 Kg/m2 at 6 months and 1.4 Kg/m2 at 12 months and a reduction of waist circumference by 2.9 cm at 6 months and 2.2 cm at 12 months; an increase of 0.1 mmol/L of HDL-C at 12 months, and decreased triglycerides (Tg) at 6 months; and decreased LDL-C and non-HDL-C at 12 months. ADLT showed a decrease of small dense-LDL-C (sdLDL-C), intermediate-density lipoprotein (IDL)-C, and HDL-Tg, and an increase of large LDL-particles (P). The er-MedDiet+PA model predicted significant reductions of Tg, sdLDL-C, VLDL-Tg and large VLDL-P in the intervention group. Conclusions: In comparison with MedDiet (control group), er-MedDiet+PA (intervention group) decreased plasma triglyceride, and triglyceride content in HDL and VLDL particles, decreased sdLDL-C, and increased large LDL particles, indicating beneficial changes against cardiovascular disease.
Internal node bagging: a layer-wise ensemble training method

When training neural networks, regularization methods are needed to avoid model overfitting. Dropout is a widely used regularization method, but its working principle is inconclusive and it does not work well for small models. This paper introduced a novel view to understand how dropout works as a layer-wise ensemble training method, that each feature in hidden layers is learned by multiple nodes, and next layer integrates the outputs of these nodes. Basing on the novel understanding of dropout, we proposed a new neural network training algorithm named internal node bagging, which explicitly forces a group of nodes to learn the same feature during training phase and combines these nodes into one node during testing phase. This means that more parameters can be used during training phase to improve the fitting ability of models while keeping model remains small during testing phase. After experimenting on three datasets, it is found that this algorithm can significantly improve the test performance of small models.
Structural Characterization and Anticomplement Activity of an Acidic Heteropolysaccharide from Lysimachia christinae Hance

Abstract A novel acidic heteropolysaccharide (LCP-90-1) was isolated and purified from a traditional “heat-clearing” Chinese medicine, Lysimachia christinae Hance. LCP-90-1 ( Mw , 20.65 kDa) was composed of Man, Rha, GlcA, Glc, Gal, and Ara, with relative molar ratios of 1.00: 3.00: 11.62: 1.31: 1.64: 5.24. The backbone consisted of 1,4- α -D-Glc p A, 1,4- α -D-Glc p , 1,4- β -L-Rha p , and 1,3,5- α -L-Ara f , with three branches of β -D-Gal p -(1 → 4)- β -L-Rha p -(1→, α -L-Ara f -(1→ and α -D-Man p -(1→ attached to the C-5 position of 1,3,5- α -L-Ara f . LCP-90-1 exhibited potent anticomplement activity (CH 50 : 135.01 ± 0.68 µg/mL) in vitro , which was significantly enhanced with increased glucuronic acid (GlcA) content in its degradation production (LCP-90-1-A, CH 50 : 28.26 ± 0.39 µg/mL). However, both LCP-90-1 and LCP90-1-A were inactivated after reduction or complete acid hydrolysis. These observations indicated the important role of GlcA in LCP-90-1 and associated derivatives with respect to anticomplement activity. Similarly, compared with LCP-90-1, the antioxidant activity of LCP-90-1-A was also enhanced. Thus, polysaccharides with a high content of GlcA might be important and effective substances of L. christinae .
Dynamics of Dressed Neurons: Modeling the Neural-Glial Circuit and Exploring its Normal and Pathological Implications

It is now established that glial cells are active partners to neurons in the nervous system. Astrocytes, a subtype of glial cell, through characteristic calcium based excitability are able to integrate the activity of neurons and thereby modulate their normal function. Quantifiable coupling schemes were developed to incorporate the role of astrocytes in neuronal dynamics. The coupling mechanism between the two cells is dynamic, bidirectional and is based on experimental data. It takes place at two distinct time scales, with the calcium activity in astrocytes occurring in seconds while the electrical activity in neurons in milliseconds. Because of the extent of their influence on neuronal dynamics astrocytes can also be thought to play a crucial role in certain neurological disorders. Basic, yet physiologically relevant circuits were constructed to explore the consequences of aberrations in neuronastrocyte coupling. Our results suggest that stronger coupling between the two cells, which takes the form of upregulation of metabotropic glutamate receptors (mGluRs) by a factor of few tens in astrocytes in our model, makes the neuron hyperexcitable and leads to self sustained (seizure like) oscillations. This prediction is consistent with the experimental observation of 20-30 times more mGluRs seen on astrocytes of epileptic tissue. Further, inhibition by interneurons in the hippocampus is an essential mechanism. The complex dichotomy of excitation and inhibition defines the normal dynamics of the brain. The inhibitive action of interneurons is also thought to provide a vital first line of defense in pathological conditions like epilepsy. The effect of local inhibition on a hyperexcitable system with enhanced astrocytic coupling was examined and it was inferred that local inhibition is unlikely to remedy the hyperexcitable system. Under normal physiological conditions astrocytes are seen to strengthen spontaneous activity of neurons, a mechanism said to be involved in plasticity and learning. Our model is able to quantitatively mimic this pattern of marked increase of spontaneous activity due to the astrocyte. Synaptic transmission is the central pathway through which information processing is carried out. The role of astrocytes in potentiating synaptic transmission was studied. The simulations carried out are a pointer to astrocytes, as playing a role in enhancing signal transmission.