Miracle-dz/UniFAR-FTUs huggingface dataset:
Combination of brinzolamide and brimonidine for glaucoma and ocular hypertension: critical appraisal and patient focus

Glaucoma is one of the leading causes of blindness and is characterized by optic nerve damage that results in visual field loss. Elevated intraocular pressure (IOP) has been associated with glaucoma progression; thus, IOP-lowering medications are the standard of care for glaucoma. Guidelines suggest monotherapy with IOP-lowering agents such as β-blockers (eg, timolol), prostaglandin analogs, carbonic anhydrase inhibitors (eg, brinzolamide), and α2-receptor agonists (eg, brimonidine). However, monotherapy may provide insufficient IOP reduction in some patients, thereby necessitating the use of multiple IOP-lowering medications. Multidrug regimens may be complex, may increase the risk of preservative-related ocular symptoms, and may potentially reduce overall drug exposure as a consequence of drug washout during closely timed sequential administrations; these difficulties may reduce overall drug efficacy and decrease patient persistence and adherence with multidrug treatment regimens. Fixed-combination medications that provide two IOP-lowering therapies within a single solution are available and may overcome some of these challenges. However, all currently available fixed combinations combine timolol with another IOP-lowering agent, indicating that additional fixed-combination alternatives would be beneficial. To meet this demand, a novel fixed combination of brinzolamide 1% and brimonidine 0.2% (BBFC) has recently been developed. In two randomized, double-masked, multinational clinical trials, BBFC had greater IOP-lowering efficacy than brinzolamide or brimonidine monotherapy after 3 months of treatment in patients with open-angle glaucoma or ocular hypertension. In both studies, the overall safety profile of BBFC was consistent with that of brinzolamide and brimonidine. Comparative studies with BBFC versus other IOP-lowering monotherapy and fixed-combination medications are not available, but the IOP reductions observed with BBFC are similar to or greater than those reported in the literature for other glaucoma treatments; thus, BBFC provides an additional fixed-combination therapeutic option for patients who require further efficacious IOP reduction and improved convenience and tolerability versus concomitant administration of two separate medications.
Multifaceted roles of aquaporins as molecular conduits in plant responses to abiotic stresses

Abstract Abiotic stress has become a challenge to food security due to occurrences of climate change and environmental degradation. Plants initiate molecular, cellular and physiological changes to respond and adapt to various types of abiotic stress. Understanding of plant response mechanisms will aid in strategies aimed at improving stress tolerance in crop plants. One of the most common and early symptoms associated with these stresses is the disturbance in plant–water homeostasis, which is regulated by a group of proteins called “aquaporins”. Aquaporins constitute a small family of proteins which are classified further on the basis of their localization, such as plasma membrane intrinsic proteins, tonoplast intrinsic proteins, nodulin26-like intrinsic proteins (initially identified in symbiosomes of legumes but also found in the plasma membrane and endoplasmic reticulum), small basic intrinsic proteins localized in ER (endoplasmic reticulum) and X intrinsic proteins present in plasma membrane. Apart from water, aquaporins are also known to transport CO2, H2O2, urea, ammonia, silicic acid, arsenite and wide range of small uncharged solutes. Besides, aquaporins also function to modulate abiotic stress-induced signaling. Such kind of versatile functions has made aquaporins a suitable candidate for development of transgenic plants with increased tolerance toward different abiotic stress. Toward this endeavor, the present review describes the versatile functions of aquaporins in water uptake, nutrient balancing, long-distance signal transfer, nutrient/heavy metal acquisition and seed development. Various functional genomic studies showing the potential of specific aquaporin isoforms for enhancing plant abiotic stress tolerance are summarized and future research directions are given to design stress-tolerant crops.
Auxiliary computations : a framework for a step-wise, non-disruptive introduction of static guarantees to untyped programs using partial evaluation techniques

Type inference can be considered a form of partial evaluation that only evaluates a program with respect to its type annotations. Building on this key observation, this dissertation presents a uniform framework for expressing computation, its dynamic properties and corresponding static type information. By using a unified approach, the static phase divide between values and types is lifted. Instead, computations and properties can be freely assigned to the static or dynamic phase of computation. Even more, moving a property from one world to the other does not require any program modifications. This thesis builds a bridge between two worlds: That of statically typed languages and the dynamically typed world. The former is wanted for the offered static guarantees and detection of a range of defects. With the increasing power of type systems available, the kinds of errors that can be statically detected is growing, nearing the goal of proving overall program correctness from the program’s source code alone. However, such power does come for a price: Type systems are becoming more complex, restrictive and invasive, to the point where specifying type annotations becomes as complex as specifying the algorithm itself. Untyped languages, in contrast, may provide less static safety but they have simpler semantics and offer a higher flexibility. They allow programmers to express their ideas without worrying about provable correctness. Not surprisingly, untyped languages have a strong following when it comes to prototyping and rapid application development. Using the framework presented in this thesis, the programmer can have both: Prototyping applications using a dynamically typed approach and gradual refinement of prototypes into programs with static guarantees. Technically, this flexibility is achieved with the novel concept of auxiliary computations. Auxiliary computation are additional streams of computation. They model, next to the data’s computation, the computation of property of data. These streams thereby may depend on the actual data that is computed, as well as on further auxiliary computations. This expressiveness brings auxiliary computations into the domain of dependent types. Partial evaluation of auxiliary computations is used to infer static knowledge from auxiliary computations. Due to the interdependencies between auxiliary computations, evaluating only those parts of a program that contribute to a property is non trivial. A further contribution of this work is the use of demands on computations to narrow the extent of partial evaluation to a single property. An algorithm for demand inference is presented and the correctness of the inferred demands is shown.
Are Large Language Models Good at Utility Judgments?

Retrieval-augmented generation (RAG) is considered to be a promising approach to alleviate the hallucination issue of large language models (LLMs), and it has received widespread attention from researchers recently. Due to the limitation in the semantic understanding of retrieval models, the success of RAG heavily lies on the ability of LLMs to identify passages with utility. Recent efforts have explored the ability of LLMs to assess the relevance of passages in retrieval, but there has been limited work on evaluating the utility of passages in supporting question answering. In this work, we conduct a comprehensive study about the capabilities of LLMs in utility evaluation for open-domain QA. Specifically, we introduce a benchmarking procedure and collection of candidate passages with different characteristics, facilitating a series of experiments with five representative LLMs. Our experiments reveal that: (i) well-instructed LLMs can distinguish between relevance and utility, and that LLMs are highly receptive to newly generated counterfactual passages. Moreover, (ii) we scrutinize key factors that affect utility judgments in the instruction design. And finally, (iii) to verify the efficacy of utility judgments in practical retrieval augmentation applications, we delve into LLMs' QA capabilities using the evidence judged with utility and direct dense retrieval results. (iv) We propose a k-sampling, listwise approach to reduce the dependency of LLMs on the sequence of input passages, thereby facilitating subsequent answer generation. We believe that the way we formalize and study the problem along with our findings contributes to a critical assessment of retrieval-augmented LLMs. Our code and benchmark can be found at \url{https://github.com/ict-bigdatalab/utility_judgments}.
Type I interferon suppresses de novo virus-specific CD4 Th1 immunity during an established persistent viral infection

Significance Potent antiviral CD4 Th1 responses generated at the onset of persistent infection are lost as infection progresses. However, it is unknown how CD4 T cell responses are mounted in the midst of an established persistent infection to restore the diminishing Th1 response. We report that an established persistent virus infection suppresses the induction and distribution of new virus-specific CD4 Th1 cells. The failure to generate new Th1 responses is mediated by chronic type I interferon (IFN-I) signaling, and its blockade effectively restored de novo Th1 development. Our study identifies a mechanism of immunosuppression and a method to restore Th1 generation during persistent infection. CD4 T cells are central to orchestrate, sustain, and potentially regenerate antiviral immunity throughout persistent viral infections. Although the evolving immune environment during persistent infection reshapes established CD4 T-cell responses, the fate of naïve CD4 T cells primed in the midst of persistent infection is unclear. We demonstrate that, in marked contrast to the onset of infection, virus-specific CD4 T cells primed during an established persistent infection have diminished ability to develop Th1 responses, to efficiently accumulate in peripheral tissues, and almost exclusively differentiate into T follicular helper cells. Consistent with suppressed Th1 and heightened Tfh differentiation, virus-specific CD4 T cells primed during the established persistent infection provide help to B cells, but only limited help to CD8 T cells. The suppression of de novo Th1 generation and tissue distribution was mediated by chronic type I IFN (IFN-I) production and was effectively restored by blocking IFN-I signaling during CD4 T-cell priming. Thus, we establish a suppressive function of chronic IFN-I signaling and mechanism of immunoregulation during an established persistent virus infection.
Welding Metallurgy and Weldability of Nickel-Base Alloys

Preface. 1. Introduction. 1.1 Ni-base Alloy Classification. 1.2 History of Nickel and Ni-base Alloys. 1.3 Corrosion Resistance. 1.4 Nickel Alloy Production. 2. Alloying Additions, Phase Diagrams, and Phase Stability. 2.1 Introduction. 2.2 General Influence of Alloying Additions. 2.3 Phase Diagrams for Solid-Solution Alloys. 2.4 Phase Diagrams for Precipitation Hardened Alloys--gamma' Formers. 2.5 Phase Diagrams for Precipitation-Hardened Alloys--gamma" Formers. 2.6 Calculated Phase Stability Diagrams. 2.7 PHACOMP Phase Stability Calculations. 3. Solid-Solution Strengthened Ni-base Alloys. 3.1 Standard Alloys and Consumables. 3.2 Physical Metallurgy and Mechanical Properties. 3.3 Welding Metallurgy. 3.4 Mechanical Properties of Weldments. 3.5 Weldability. 3.6 Corrosion Resistance. 3.7 Case Studies. 4. Precipitation Strengthened Ni-base Alloys. 4.1 Standard Alloys and Consumables. 4.2 Physical Metallurgy and Mechanical Properties. 4.3 Welding Metallurgy. 4.4 Mechanical Properties of Weldments. 4.5 Weldability. 5. Oxide Dispersion Strengthened Alloys and Nickel Aluminides. 5.1 Oxide Dispersion Strengthened Alloys. 5.2 Nickel Aluminide Alloys. 6. Repair Welding of Ni-base Alloys. 6.1 Solid-Solution Strengthened Alloys. 6.2 Precipitation Strengthened Alloys. 6.3 Single Crystal Superalloys. 7. Dissimilar Welding. 7.1 Application of Dissimilar Welds. 7.2 Influence of Process Parameters on Fusion Zone Composition. 7.3 Carbon, Low Alloys and Stainless Steels. 7.4 Postweld Heat Treatment Cracking in Stainless Steels Welded with Ni-base Filler Metals. 7.5 Super Austenitic Stainless Steels. 7.6 Dissimilar Welds in Ni-base Alloys - Effect on Corrosion Resistance. 7.7 9%Ni Steels. 7.8 Super Duplex Stainless Steels. 7.9 Case Studies. 8. Weldability Testing. 8.1 Introduction. 8.2 The Varestraint Test. 8.3 Modified Cast Pin Tear Test. 8.4 The Sigmajig Test. 8.5 The Hot Ductility Test. 8.6 The Strain-to-Fracture Test. 8.7 Other Weldability Tests. Appendix A Composition of Wrought and Cast Nickel-Base Alloys. Appendix B Composition of Nickel and Nickel Alloy Consumables. Appendix C Corrosion Acceptance Testing Methods. Appendix D Etching Techniques for Ni-base Alloys and Welds. Author Index. Subject Index.
Covariation of axon initial segment location and dendritic tree normalizes the somatic action potential

Significance Neurons generate highly reliable and temporally precise action potentials with a spatial onset in the axon initial segment. The axon initial segment location relative to the soma is, however, highly variable across neurons within the same cell class. Here, we experimentally and theoretically investigated the structure–function relationship of axon distances in neocortical pyramidal neurons. We discovered a scaling principle between the size of the dendritic tree and the axon distance supported by the cable properties and electrophysiological recordings. The work reveals that axons are not randomly positioned but covary with dendrites normalizing the somatic action potential in the face of diverse cellular morphologies. In mammalian neurons, the axon initial segment (AIS) electrically connects the somatodendritic compartment with the axon and converts the incoming synaptic voltage changes into a temporally precise action potential (AP) output code. Although axons often emanate directly from the soma, they may also originate more distally from a dendrite, the implications of which are not well-understood. Here, we show that one-third of the thick-tufted layer 5 pyramidal neurons have an axon originating from a dendrite and are characterized by a reduced dendritic complexity and thinner main apical dendrite. Unexpectedly, the rising phase of somatic APs is electrically indistinguishable between neurons with a somatic or a dendritic axon origin. Cable analysis of the neurons indicated that the axonal axial current is inversely proportional to the AIS distance, denoting the path length between the soma and the start of the AIS, and to produce invariant somatic APs, it must scale with the local somatodendritic capacitance. In agreement, AIS distance inversely correlates with the apical dendrite diameter, and model simulations confirmed that the covariation suffices to normalize the somatic AP waveform. Therefore, in pyramidal neurons, the AIS location is finely tuned with the somatodendritic capacitive load, serving as a homeostatic regulation of the somatic AP in the face of diverse neuronal morphologies.
The Origins of Campaign Agendas

Why and how do candidates choose the issues on which their campaigns are based? Drawing on a large database of candidate advertisements from the 1998 House and Senate campaigns, extant theories of issue emphasis, which focus on factors such as party ownership and candidate record, are tested here and these theories are expanded by examining in more detail the role of constituency characteristics. Most notably, party ownership’s impact is demonstrated to be weak: candidates are more willing to ‘trespass’ or talk about the other party’s issues than previous literature has found. Also ‘trespassing’ is shown to be facilitated by framing the other party’s issues in certain ways. The results have implications for theories of candidate strategy and for normative questions, such as how much ‘dialogue’ occurs in campaigns. One chief function of electoral campaigns is to place issues before voters. Given that most voters are relatively inattentive to politics, campaigns provide a crucial arena for candidates to discuss their views on specific issues. Commentators in turn refer to the agendas that candidates formulate as ‘what this election is about’. Campaign agendas also resonate beyond the campaign as elected officials arrive in various capitals and draw on these agendas to guide policy making. Campaign agendas take on even greater import because there are electoral benefits to agenda setting. Candidates can win votes by emphasizing issues where they perceive an advantage, thereby making these issues prominent in voters’ minds. This strategy is an appealing alternative to other, arguably more difficult tactics, such as shifting one’s own position as a candidate to match the voters’ or persuading voters to adopt a specific position on an issue. As candidates begin to formulate agendas, salient political events and public opinion are very much on their minds. For example, events such as a war or an economic recession often figure prominently in campaign agendas. Candidates also consult the electorate; answers to a polling question like ‘What do you think is the most important problem facing our country? ’ may lead candidates to profess similar concerns. These kinds of factors undoubtedly contribute to variation in campaign agendas across election years. However, these factors may not fully explain variation among candidates within any given election. Salient events and the public’s agenda are often national in scope and should
Exploring Causal Factors of DBMS Thrashing

Modern DBMSes are designed to support many transactions running simultaneously. DBMS thrashing is indicated by the existence of a sharp drop in transaction throughput. The thrashing behavior in DBMSes is a serious concern to DBAs engaged in on-line transaction processing (OLTP) and on-line analytical processing (OLAP) systems, as well as to DBMS implementors developing technologies related to concurrency control. If thrashing is prevalent in a DBMS, thousands of transactions may be aborted, resulting in little progress in transaction throughput over time. From an engineering perspective, therefore, it is of critical importance to understand the factors of DBMS thrashing. However, understanding the origin of modern DBMSes’ thrashing is challenging, due to many factors that may interact. The existing literature on thrashing exhibits the following weaknesses: (i) methodologies have been based on simulation and analytical studies, rather than on empirical analysis on real DBMSes, (ii) scant attention has been paid to the associations between factors, and (iii) studies have been restricted to one specific DBMS rather than across multiple DBMSes. This dissertation aims at better understanding the thrashing phenomenon across multiple DBMSes. We identify the underlying causes and propose a novel structural causal model to explicate the relationships between various factors contributing to DBMS thrashing. Our model derives a number of specific hypotheses to be subsequently tested across DBMSes, providing empirical support for this model as well as engineering implications for fundamental improvements in transaction processing. Our model also guides database researchers to refine this causal model, by looking into other unknown factors.
Evaluation of communication latency in industrial IoT applications

The idea of Industry 4.0 includes the concept of Industrial Internet of Things (IIoT) that is the possibility for industrial devices to have Internet connection and share data. Huge amount of data are stored and analyzed in the Cloud to extract meaningful information to be sold as "services". Today, many Industry 4.0 scenarios do not require a short latency between data collection and output reaction, but it is expected that short latency services would be seen by the market as a distinctive quality. This paper deals with the estimation of latency in transferring data from the field (where the production takes place) to the Cloud and then back to field. Since IIoT natively refers to worldwide applications, the paper analyzes some cases where interacting nodes are deployed in different continents. The experimental results show that simple solutions based on widely accepted lightweight protocols (e.g. MQTT) and inexpensive industrial grade IoT devices are feasible. From the performance point of view, when using free access Cloud servers, they can achieve round trip latency down to 300 ms with standard deviation of about 20 ms over one-week observation time.
The role of insight in perceptual learning: evidence from illusory contour perception

The distinction between gradual and abrupt improvement in performance is commonly made in behavioral studies of learning. The learning of perceptual and motor skills is often characterized by gradual, incremental improvement and is found not to generalize over stimulus manipulations such as change in retinal size or location. In contrast, marked improvement in performance can occur suddenly—a phenomenon that has been termed ‘‘insight. ’’ Previously, insight has been studied in the context of problem solving and similar cognitive-level tasks. In this chapter, we use an illusory contours shape-discrimination task to present evidence that perceptual learning can exhibit characteristics of insight. Observers exhibited an abrupt, dramatic improvement in their performance, which resembled an incident of insight. At the same time, however, the improvement showed a degree of stimulus specificity that previously was thought to characterize incremental, gradual learning. This juxtaposition of abrupt and stimulus-specific improvement suggests that the dichotomy between the two forms of learning needs to be revised. This idea echoes Hebb (1949), who argued that the insight/incremental-learning dichotomy may be artificial and that the two forms of learning need to be addressed within a single theoretical framework. In terms of brain mechanisms, this means that all types of learning may involve interactions between low-level and high-level representations of the stimulus.
Language Modeling with Deep Transformers

We explore deep autoregressive Transformer models in language modeling for speech recognition. We focus on two aspects. First, we revisit Transformer model configurations specifically for language modeling. We show that well configured Transformer models outperform our baseline models based on the shallow stack of LSTM recurrent neural network layers. We carry out experiments on the open-source LibriSpeech 960hr task, for both 200K vocabulary word-level and 10K byte-pair encoding subword-level language modeling. We apply our word-level models to conventional hybrid speech recognition by lattice rescoring, and the subword-level models to attention based encoder-decoder models by shallow fusion. Second, we show that deep Transformer language models do not require positional encoding. The positional encoding is an essential augmentation for the self-attention mechanism which is invariant to sequence ordering. However, in autoregressive setup, as is the case for language modeling, the amount of information increases along the position dimension, which is a positional signal by its own. The analysis of attention weights shows that deep autoregressive self-attention models can automatically make use of such positional information. We find that removing the positional encoding even slightly improves the performance of these models.