Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributionally Robust Chance-Constrained Optimal Transmission Switching for Renewable Integration

Increasing integration of renewable generation poses significant challenges to ensure robustness guarantees in real-time energy system decision-making. This work aims to develop a robust optimal transmission switching (OTS) framework that can effectively relieve grid congestion and mitigate renewable curtailment. We formulate a two-stage distributionally robust chance-constrained (DRCC) problem that assures limited constraint violations for any uncertainty distribution within an ambiguity set. Here, the second-stage recourse variables are represented as linear functions of uncertainty, yielding an equivalent reformulation involving linear constraints only. We utilize moment-based (mean-mean absolute deviation) and distance-based ($\infty$-Wasserstein distance) ambiguity sets that lead to scalable mixed-integer linear program (MILP) formulations. Numerical experiments on the IEEE 14-bus and 118-bus systems have demonstrated the performance improvements of the proposed DRCC-OTS approaches in terms of guaranteed constraint violations and reduced renewable curtailment. In particular, the computational efficiency of the moment-based MILP approach, which is scenario-free with fixed problem dimensions, has been confirmed, making it suitable for real-time grid operations.
Augmented Reality Application for Architects and interior designers: Interno A cost effective solution

Nowadays with excessive work load and busy life, many professional face problems that results in the loss of their clients or the certain overheads that spoil the process of satisfying the client. The proposed software will be used by interior designers or architects. This proposed research most likely acts as an effective tool which can decrease the gap between industrial company and customer in addition to other applicable business communities. It will help in visualizing architect plans and interior designs. A virtual model of real environment can be designed before its physical implementation, it will allow interior designers to implement their idea in the given workspace virtually and then view it in real environment, it will also allow architects to view their 3D visualizations on their 2D drawings. Application is based on my findings of user's expectations of an augmented reality interior design service, a service which is a combination of various functionality of social media, augmented reality (AR) and 3-D modeling that encloses the concept of home design. This study distinctively bridges all users of relevant businesses to the user-intensive design of an augmented reality. The paper provides you with the inner depth on how the augmented reality can be implemented to facilitate the architects and interior designers as well it discusses the algorithm used to achieve the functionalities. The proposed application exhibits two types of Augmented reality, Marker less and marker based. The novelty of the project is that it does not require any sort of expensive gadgets. It can easily be used via smartphones and tablets. It is also operable on any operating system. This is a cost-effective solution that primarily reduces the overheads that interior designer and architects confronts on daily basis. The software exhibits all the features that might be required by interior designers and architects respectively.
An Algebraic Method to Identify Classes of Formulas in Calculus of Predicates( Bilevel Programming, Optimization Methods, and Applications to Economics)

The P-complete problem of logic deduction in classical propositional and first order predicate calculus is considered. The suggested method is alternative to the traditional methods of direct and inverse logic deduction in particular to the Robinson’s resolution principle. The deterministic algorithm of polynomial complexity based on Boolean algebra of cubic functions for differentiation between two classes of formulas: valid and satisfiable, or unsatisfiable and satisfiable, is suggested.
Optimising Real-World Traffic Cycle Programs by Using Evolutionary Computation

Traffic congestion, and the consequent loss of time, money, quality of life, and higher pollution, is currently one of the most important problems in cities, and several approaches have been proposed to reduce it. In this paper, we propose a novel formulation of the traffic light scheduling problem in order to alleviate it. This novel formulation of the problem allows more realistic scenarios to be modeled, and as a result, it becomes much harder to solve in comparison to previous formulations. The proposal of more advanced and efficient techniques than those applied in past research is thus required. We propose the application of diversity-based multi-objective optimizers, which have shown to provide promising results when addressing single-objective problems. The wide experimental evaluation performed over a set of real-world instances demonstrates the good performance of our proposed diversity-based multi-objective method to tackle traffic at a large scale, especially in comparison to the best-performing single-objective optimizer previously proposed in the literature. Consequently, in this paper, we provide new state-of-the-art algorithmic schemes to address the traffic light scheduling problem that can deal with a whole city, instead of just a few streets and junctions, with a higher level of detail than the one found in present studies due to our micro-analysis of streets.
Understanding the Differences Behind One Step and Two Steps Strategies in Speech Quality Evaluation

Strategies used in methods for objective speech quality evaluation can be classified into two main categories namely one step and two-step strategy. The one-step strategy aims at an algorithm or structure which transforms speech representation directly into a scalar, and the two-steps strategy often divides the evaluation procedure into two subsequent stages. Generally speaking, it constructs firstly objective measurements predefined for the disturbance within speech signal, and then accumulates the measurements to a single value which is similar to the opinion score. The two-step strategy has been developed ahead of one step strategy, leading to the study of the one step strategy. This paper describes the principles and essential elements in these strategies, compares the differences between them, and analyses the merits and drawbacks in these methods. Some criteria regarding to the method selection in speech quality evaluation which are based mainly on the research scenario are suggested at the end of the paper.
Cohort Profile: Swiss BioRef: The building blocks of a nationwide IT infrastructure in Switzerland for generating precise reference intervals

Purpose: Swiss BioRef is a nation-wide multicenter infrastructure project, the aim of which is to become a sustainable framework for the estimation and assessment of patient-group-specific reference intervals in laboratory medicine and beyond. In this unprecedented effort, nation-wide multidimensional data from multiple clinical laboratory databases has been combined under the common interoperable semantic framework of the Swiss Personalized Health Network (SPHN) initiative. The consolidated effort enables creating extremely detailed patient group-specific queries via intuitive web applications, allowing the generation of individualised, covariate adjusted reference intervals on-the-fly. Participants: The project is a collaborative effort of four major hospitals in Switzerland, the University Hospital Bern (Inselspital, Insel), University Hospital Lausanne (CHUV), Swiss Spinal Cord Injury Cohort (SwiSCI) and the University Children's Hospital Zurich (KiSpi), and two academic groups in Bern and in Lausanne. Findings to date: Within the infrastructure we deployed, the laboratory data from four major hospitals (approximately 9 million measurements from 250'000 patients) is made available to two conceptually different web applications (one centralised and statistically detailed, one decentralised using distributed computing). They enable the inference of reference intervals for more than 40 blood test variables from clinical chemistry, hematology, point-of-care-testing and coagulation testing, with various patient factors (such as age, sex and a combination of ICD-10 defined diagnoses) and analytical factors (such as type or unique identifiers) that can be used to generate precise reference intervals for the respective groups. Future plans: Now that all required basic infrastructure elements for Swiss BioRef are deployed, we are evaluating inter-cohort transferability of semantic standards, change tracking in merged databases and biological variation of the blood test variables, in order to generate precise reference intervals. While adjusting the developed web-interfaces to suit the needs of the various end-users, we additionally plan to onboard new national and international partners.
Physiological Robustness of Model Gram-Negative Bacteria in Response to Genome Rewiring

DNA supercoiling and nucleoid-associated proteins (NAPs) are two of the factors that govern the architecture of the bacterial genome, influencing the expression of the genetic information that it contains. Alterations to DNA topology, and to the numbers and types of NAPs, have pleiotropic effects on gene expression, suggesting that modifications to the production patterns of DNA topoisomerases and/or NAPs are likely to result in marked impacts on bacterial physiology. Knockout mutations in the genes encoding these proteins (where the mutants remain viable) result in clear physiological effects. However, genetic modifications that involve rewiring, or repositioning, of topoisomerase or NAP genes produce much more subtle outcomes. These findings demonstrate that the high-level regulatory circuitry of bacteria is robust in the face of genomic rearrangements that, a priori, might be expected to produce significant changes in bacterial lifestyle. Examples from genomic rewiring experiments, performed chiefly with the Gram-negative model bacteria Escherichia coli K-12 and Salmonella enterica serovar Typhimurium, will be used to illustrate these features. The results show not only the ability of naturally occurring bacteria to tolerate regulatory rewiring but also indicate the limits within which experiments in synthetic biology may be designed.
Connectivity-Defined Subdivisions of the Intraparietal Sulcus Respond Differentially to Abstraction during Decision-Making

The intraparietal sulcus (IPS) has been implicated in numerous functions that range from representation of visual stimuli to action planning, but its role in abstract decision-making has been unclear, in part because low-level functions often act as confounds. Here, we address this problem using a task that dissociates abstract decision-making from sensory salience, attentional control, motor planning, and motor output. Functional MRI data were collected from healthy female and male human subjects while they performed a policy abstraction task requiring use of a more abstract (second-order) rule to select between two less abstract (first-order) rules that informed the motor response. By identifying IPS subdivisions with preferential connectivity to prefrontal regions that are differentially responsive to task abstraction, we found that a caudal IPS (cIPS) subregion with strongest connectivity to the pre-premotor cortex was preferentially active for second-order cues, whereas a rostral IPS subregion (rIPS) with strongest connectivity to the dorsal premotor cortex was active during attentional control over first-order cues. These effects for abstraction were seen in addition to cIPS activity that was specific to sensory salience, and rIPS activity that was specific to motor output. Notably, topographic responses to the second-order cue were detected along the caudal-rostral axis of IPS, mirroring the broader organization seen in lateral prefrontal cortex. Together, these data demonstrate that subregions within IPS exhibit activity responsive to policy abstraction, and they suggest that IPS may be organized into frontoparietal subnetworks that support hierarchical cognitive control. SIGNIFICANCE STATEMENT Abstract decision-making allows us to flexibly adapt our behavior to new contexts. Although much previous work has focused on the role of lateral prefrontal cortex in such decisions, the contributions of parietal cortex have been relatively understudied. Here, we demonstrate that spatially segregated subregions of human IPS with strong functional connections to lateral prefrontal cortex demonstrate activity selective for abstract decisions. This activity can be distinguished from responses resulting from cognitive processes related to sensory salience, attentional control, motor planning, and movement. Together, these findings indicate that different task demands are reflected in the topography of IPS, and they explicitly reveal a role in abstract decision-making.
The Impact of Internal Solitary Waves on the Nutrient Circulation System

Internal waves in lakes and oceans are ubiquitous whenever a density stratification is present. These waves are relatively slow moving (compared to surface water waves), can be large in extent and have long time scales. As these waves are so common, it is known that they play a role in recirculating nutrients throughout the water column. The various factors contributing to this recirculation are commonly referred to as the nutrient circulation system. This thesis analyses three potential mechanisms of internal wave influence on the nutrient circulation system. Surface water waves have been well known to influence the nutrient circulation system, especially in shallow regions where wave breaking occurs. However, internal water waves can affect the flow of lake nutrients in deeper water where surface waves will have a negligible effect. In this thesis, we use pseudospectral methods to analyze internal wave induced fluid flow within the water column of a lake or ocean, within the bottom boundary layer and within the sub-fluid porous layer. These three regimes represent significantly differing length scales within lake and ocean systems. In all cases presented, we assume that the water column is deep enough that we can neglect the effect of surface water waves. Previous literature indicates that internal waves of sufficient size can induce the formation and bursting of separation bubbles near the bottom boundary layer. These bursting events have the potential to induce significant resuspension of sediment back into the water column. We explicitly model shear induced resuspension and demonstrate that only internal waves of sufficient magnitude can induce true resuspension. We present a parameterization of the non-dimensional parameter regime required for resuspension. These bursting events are always associated with vortex production near the bottom boundary. Near the lake bottom, a layer of fluid mud is present which is known to be non-Newtonian in nature. The non-Newtonian properties of the fluid preserve the small scale features of the flow and locally change the Reynolds number and thereby facilitate more energetic flows on shorter length scales. We thus demonstrate that the vortices found within the fluid mud region have the potential to induce substantial subsequent resuspension. It is shown that the non-Newtonian effects are even substantive enough to overcome an increase in viscosity near the bottom layer. Beneath the free flowing fluid in lakes and oceans, there often exists a porous layer composed of settled particulate matter. Darcy’s law is an empirically determined relationship between the seepage rates found within such a porous layer and the pressure. Due to their large amplitude, internal waves can have produce a significant pressure signature on
Brain-wide functional connectivity of face patch neurons during rest

Significance In resting state functional magnetic resonance imaging (fMRI), areas showing coherent hemodynamic fluctuations across the brain are operationally defined to be functionally connected. However, it is unknown how the activity of single units residing within a voxel contributes to this network structure. Here we demonstrate a shared but restricted pattern of functional connectivity among neighboring neurons residing in functionally defined face patches. Unexpectedly, such neurons also exhibited a prominent inverse correlation with thalamic structures and brainstem neuromodulatory centers. Single unit maps differed from analogous maps obtained with local field potentials and seed-based fMRI. These findings suggest that during rest, individual cortical neurons have a restricted set of functional connections, which is governed in part by anatomical projections and in part by neuromodulation.
Liposomal T cell engager and re-director for tumor cell eradication in cancer immunotherapy

ABSTRACT T cells are one of the most important effector cells in cancer immunotherapy. Various T cell-dependent bispecific antibody (TDB) drugs that engage T cells for targeted cancer cell lysis are being developed. Here, we describe supra-molecular T-cell redirecting antibody fragment-anchored liposomes (TRAFsomes) and report their immune modulation and anti-cancer effects. We found that TRAFsomes containing different copies of anti-CD3 fragments displayed different T cell modulation profiles, showing that optimization of surface density is needed to define the therapeutic window for potentiating cancer cell-specific immune reactions while minimizing nonspecific side effects. Moreover, small molecular immunomodulators may also be incorporated by liposomal encapsulation to drive CD8 + T cell biased immune responses. In vivo studies using human peripheral blood mononuclear cell reconstituted mouse models showed that TRAFsomes remained bounded to human T cells and persisted for more than 48 hours after injection. However, only TRAFsomes containing a few anti-CD3 (n = 9) demonstrated significant T cell-mediated anti-cancer activities to reverse tumor growth. Those with more anti-CD3s (n = 70) caused tumor growth and depletion of human T cells at the end of treatments. These data suggested that TRAFsomes can be as potent as traditional TDBs and the liposomal structure offers great potential for immunomodulation and improvement of the therapeutic index. Abbreviation: Chimeric antigen receptor T cells (CAR-T cells), Cytokine release syndrome (CRS) Cytotoxic T cell (CTL) Effector: target ratios (E:T ratios), Heavy chain (HC) Immune-related adverse events (irAE), Large unilamellar vesicle (LUV), Peripheral blood mononuclear cells (PBMCs, Single-chain variable fragment (scFv), T cell-dependent bispecific antibody (TDB), T cell redirecting antibody fragment-anchored liposomes (TRAFsomes), Methoxy poly-(ethylene glycol) (mPEG)
Intensity of repetitive negative thinking in depression is associated with greater functional connectivity between semantic processing and emotion regulation areas

Abstract Background Repetitive negative thinking (RNT), a cognitive process that encompasses past (rumination) and future (worry) directed thoughts focusing on negative experiences and the self, is a transdiagnostic construct that is especially relevant for major depressive disorder (MDD). Severe RNT often occurs in individuals with severe levels of MDD, which makes it challenging to disambiguate the neural circuitry underlying RNT from depression severity. Methods We used a propensity score, i.e., a conditional probability of having high RNT given observed covariates to match high and low RNT individuals who are similar in the severity of depression, anxiety, and demographic characteristics. Of 148 MDD individuals, we matched high and low RNT groups (n = 50/group) and used a data-driven whole-brain voxel-to-voxel connectivity pattern analysis to investigate the resting-state functional connectivity differences between the groups. Results There was an association between RNT and connectivity in the bilateral superior temporal sulcus (STS), an important region for speech processing including inner speech. High relative to low RNT individuals showed greater connectivity between right STS and bilateral anterior insular cortex (AI), and between bilateral STS and left dorsolateral prefrontal cortex (DLPFC). Greater connectivity in those regions was specifically related to RNT but not to depression severity. Conclusions RNT intensity is directly related to connectivity between STS and AI/DLPFC. This might be a mechanism underlying the role of RNT in perceptive, cognitive, speech, and emotional processing. Future investigations will need to determine whether modifying these connectivities could be a treatment target to reduce RNT.
A Class of Iterative Solvers for the Helmholtz Equation: Factorizations, Sweeping Preconditioners, Source Transfer, Single Layer Potentials, Polarized Traces, and Optimized Schwarz Methods

Solving time-harmonic wave propagation problems by iterative methods is a difficult task, and over the last two decades, an important research effort has gone into developing preconditioners for the simplest representative of such wave propagation problems, the Helmholtz equation. A specific class of these new preconditioners are considered here. They were developed by researchers with various backgrounds using formulations and notations that are very different, and all are among the most promising preconditioners for the Helmholtz equation. The goal of the present manuscript is to show that this class of preconditioners are based on a common mathematical principle, and they can all be formulated in the context of domain decomposition methods called optimized Schwarz methods. This common formulation allows us to explain in detail how and why all these methods work. The domain decomposition formulation also allows us to avoid technicalities in the implementation description we give of these recent methods. The equivalence of these methods with optimized Schwarz methods translates at the discrete level into equivalence with approximate block LU decomposition preconditioners, and we give in each case the algebraic version, including a detailed description of the approximations used. While we chose to use the Helmholtz equation for which these methods were developed, our notation is completely general and the algorithms we give are written for an arbitrary second order elliptic operator. The algebraic versions are even more general, assuming only a connectivity pattern in the discretization matrix.
Gender-Based Violence, Subjective Quality of Life, and Mental Health Outcomes Among Palestinian Women: The Mediating Role of Social Support and Agency

We tested the association between gender-based violence (GBV), subjective quality of life, and mental distress manifested by anxiety, depression, and stress among Palestinian women exposed to political and military violence. Depression, Anxiety and Stress Scale-21, Berlin Social Support Scales, WHO-5 subjective Quality of Life Scale, Women's Agency Scale 61, and Violence Against Women Questionnaire were administered to 332 purposely selected participants. Structural equation modeling was applied to address the study hypothesis. A conceptual model depicting GBV as a predictor, mental distress as an outcome variable, and agency and social support as mediators was confirmed.