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Gellan gum has gained significant attention due to its versatility in multiple applications in the form of hydrogels and microgels. A thorough understanding of the rheological behaviour of these systems is crucial both for fundamental research and to optimize the manufacturing needs. To this aim, here we extensively characterize the rheological behaviour of gellan based hydrogels and microgels recently used for efficient paper cleaning for restoration interventions. In particular, we study their viscoelastic properties, also during hydrogel and microgel formation, assessing the role of temperature, gellan concentration, and, importantly, the presence of different cations, which plays a crucial role in the gelation process. We find the interesting result that, in the conditions where they are efficient for cleaning, gellan hydrogels exhibit a double yielding behavior. In addition, we provide a detailed description of gellan microgels preparation, ensuring high control and reproducibility of the samples. Altogether our study sheds light on the mechanical stability, network structure, and overall functionality of the gellan-based gels, providing valuable insights into optimizing conditions for desired applications in paper cleaning.

A $(v,k;r)$ Heffter space is a resolvable $(v_r,b_k)$ configuration whose points form a half-set of an abelian group $G$ and whose blocks are all zero-sum in $G$. It was recently proved that there are infinitely many orders $v$ for which, given any pair $(k,r)$ with $k\geq3$ odd, a $(v,k;r)$ Heffter space exists. This was obtained by imposing a point-regular automorphism group. Here we relax this request by asking for a point-semiregular automorphism group. In this way the above result is extended also to the case $k$ even., Comment: 8 pages

Quantum programs are typically developed using quantum Software Development Kits (SDKs). The rapid advancement of quantum computing necessitates new tools to streamline this development process, and one such tool could be Generative Artificial intelligence (GenAI). In this study, we introduce and use the Qiskit HumanEval dataset, a hand-curated collection of tasks designed to benchmark the ability of Large Language Models (LLMs) to produce quantum code using Qiskit - a quantum SDK. This dataset consists of more than 100 quantum computing tasks, each accompanied by a prompt, a canonical solution, a comprehensive test case, and a difficulty scale to evaluate the correctness of the generated solutions. We systematically assess the performance of a set of LLMs against the Qiskit HumanEval dataset's tasks and focus on the models ability in producing executable quantum code. Our findings not only demonstrate the feasibility of using LLMs for generating quantum code but also establish a new benchmark for ongoing advancements in the field and encourage further exploration and development of GenAI-driven tools for quantum code generation.

Code Large Language Models (Code LLMs) have emerged as powerful tools, revolutionizing the software development landscape by automating the coding process and reducing time and effort required to build applications. This paper focuses on training Code LLMs to specialize in the field of quantum computing. We begin by discussing the unique needs of quantum computing programming, which differ significantly from classical programming approaches or languages. A Code LLM specializing in quantum computing requires a foundational understanding of quantum computing and quantum information theory. However, the scarcity of available quantum code examples and the rapidly evolving field, which necessitates continuous dataset updates, present significant challenges. Moreover, we discuss our work on training Code LLMs to produce high-quality quantum code using the Qiskit library. This work includes an examination of the various aspects of the LLMs used for training and the specific training conditions, as well as the results obtained with our current models. To evaluate our models, we have developed a custom benchmark, similar to HumanEval, which includes a set of tests specifically designed for the field of quantum computing programming using Qiskit. Our findings indicate that our model outperforms existing state-of-the-art models in quantum computing tasks. We also provide examples of code suggestions, comparing our model to other relevant code LLMs. Finally, we introduce a discussion on the potential benefits of Code LLMs for quantum computing computational scientists, researchers, and practitioners. We also explore various features and future work that could be relevant in this context.

We consider a setup with Internet of Things (IoT), where a base station (BS) collects data from nodes that use two different communication modes. The first is pull-based, where the BS retrieves the data from specific nodes through queries. In addition, the nodes that apply pull-based communication contain a wake-up receiver: upon a query, the BS sends wake-up signal (WuS) to activate the corresponding devices equipped with wake-up receiver (WuDs). The second one is push-based communication, in which the nodes decide when to send to the BS. Consider a time-slotted model, where the time slots in each frame are shared for both pull-based and push-based communications. Therein, this coexistence scenario gives rise to a new type of problem with fundamental trade-offs in sharing communication resources: the objective to serve a maximum number of queries, within a specified deadline, limits the transmission opportunities for push sensors, and vice versa. This work develops a mathematical model that characterizes these trade-offs, validates them through simulations, and optimizes the frame design to meet the objectives of both the pull- and push-based communications., Comment: Paper submitted to the 25th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2024). Copyright may be transferred without further notice

In a nesting of a balanced incomplete block design (or BIBD), we wish to add a point (the \emph{nested point}) to every block of a $(v,k,\lambda)$-BIBD in such a way that we end up with a partial $(v,k+1,\lambda+1)$-BIBD. In the case where the partial $(v,k+1,\lambda+1)$-BIBD is in fact a $(v,k+1,\lambda+1)$-BIBD, we have a \emph{perfect nesting}. We show that a nesting is perfect if and only if $k = 2 \lambda + 1$. Perfect nestings were previously known to exist in the case of Steiner triple systems (i.e., $(v,3,1)$-BIBDs) when $v \equiv 1 \bmod 6$, as well as for some symmetric BIBDs. Here we study nestings of $(v,4,1)$-BIBDs, which are not perfect nestings. We prove that there is a nested $(v,4,1)$-BIBD if and only if $v \equiv 1 \text{ or } 4 \bmod 12$, $v \geq 13$. This is accomplished by a variety of direct and recursive constructions.

The availability of Large Language Models (LLMs) which can generate code, has made it possible to create tools that improve developer productivity. Integrated development environments or IDEs which developers use to write software are often used as an interface to interact with LLMs. Although many such tools have been released, almost all of them focus on general-purpose programming languages. Domain-specific languages, such as those crucial for Information Technology (IT) automation, have not received much attention. Ansible is one such YAML-based IT automation-specific language. Ansible Lightspeed is an LLM-based service designed explicitly to generate Ansible YAML given natural language prompt. This paper first presents the design and implementation of the Ansible Lightspeed service. We then evaluate its utility to developers using diverse indicators, including extended utilization, analysis of user rejected suggestions, as well as analysis of user sentiments. The analysis is based on data collected for 10,696 real users including 3,910 returning users. The code for Ansible Lightspeed service and the analysis framework is made available for others to use. To our knowledge, our study is the first to involve thousands of users in evaluating code assistants for domain-specific languages. We propose an improved version of user acceptance rate and we are the first code completion tool to present N-Day user retention figures. With our findings we provide insights into the effectiveness of small, dedicated models in a domain-specific context. We hope this work serves as a reference for software engineering and machine learning researchers exploring code completion services for domain-specific languages in particular and programming languages in general.

In upcoming 6G networks, unmanned aerial vehicles (UAVs) are expected to play a fundamental role by acting as mobile base stations, particularly for demanding vehicle-to-everything (V2X) applications. In this scenario, one of the most challenging problems is the design of trajectories for multiple UAVs, cooperatively serving the same area. Such joint trajectory design can be performed using multi-agent deep reinforcement learning (MADRL) algorithms, but ensuring collision-free paths among UAVs becomes a critical challenge. Traditional methods involve imposing high penalties during training to discourage unsafe conditions, but these can be proven to be ineffective, whereas binary masks can be used to restrict unsafe actions, but naively applying them to all agents can lead to suboptimal solutions and inefficiencies. To address these issues, we propose a rank-based binary masking approach. Higher-ranked UAVs move optimally, while lower-ranked UAVs use this information to define improved binary masks, reducing the number of unsafe actions. This approach allows to obtain a good trade-off between exploration and exploitation, resulting in enhanced training performance, while maintaining safety constraints., Comment: Accepted for the 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024)

The rapid expansion of connected and autonomous vehicles (CAVs) and the shift towards millimiter-wave (mmWave) frequencies offer unprecedented opportunities to enhance road safety and traffic efficiency. Sidelink communication, enabling direct Vehicle-to-Vehicle (V2V) communications, play a pivotal role in this transformation. As communication technologies transit to higher frequencies, the associated increase in bandwidth comes at the cost of a severe path and penetration loss. In response to these challenges, we investigate a network configuration that deploys beamforming-capable Unmanned Aerial Vehicles (UAVs) as relay nodes. In this work, we present a comprehensive analytical framework with a groundbreaking performance metric, i.e. average access probability, that quantifies user satisfaction, considering factors across different protocol stack layers. Additionally, we introduce two Radio Resources Assignment (RRA) methods tailored for UAVs. These methods consider parameters such as resource availability, vehicle distribution, and latency requirements. Through our analytical approach, we optimize the average access probability by controlling UAV altitude based on traffic density. Our numerical findings validate the proposed model and strategy, which ensures that Quality of Service (QoS) standards are met in the domain of Vehicle-to-Anything (V2X) sidelink communications.

The notion of a Heffter array, which received much attention in the last decade, is equivalent to a pair of orthogonal Heffter systems. In this paper we study the existence problem of a set of $r$ mutually orthogonal Heffter systems for any $r$. Such a set is equivalent to a resolvable partial linear space of degree $r$ whose parallel classes are Heffter systems: this is a new combinatorial design that we call a Heffter space. We present a series of direct constructions of Heffter spaces with block size odd and arbitrarily large degree $r$ obtained with the crucial use of finite fields. Among the applications we establish, in particular, the existence of $r$ mutually orthogonal $k$-cycle systems of order a prime power $q=2kw+1$ whenever $kw$ is odd and $w>4k^4\lceil{r\over k}\rceil$.

We present some results on the harmonious colorings of the Levi graph of a $2$-design, focusing on Steiner $2$-designs. It is easily seen that the harmonious chromatic number of such a Levi graph is at least the number of points of the design: we study and construct Banff designs, that is, designs such that this lower bound is attained.

Large language models (LLMs) have become remarkably good at improving developer productivity for high-resource programming languages. These models use two kinds of data: large amounts of unlabeled code samples for pre-training and relatively smaller amounts of labeled code samples for fine-tuning or in-context learning. Unfortunately, many programming languages are low-resource, lacking labeled samples for most tasks and often even lacking unlabeled samples. Therefore, users of low-resource languages (e.g., legacy or new languages) miss out on the benefits of LLMs. Cross-lingual transfer uses data from a source language to improve model performance on a target language. It has been well-studied for natural languages, but has received little attention for programming languages. This paper reports extensive experiments on four tasks using a transformer-based LLM and 11 to 41 programming languages to explore the following questions. First, how well does cross-lingual transfer work for a given task across different language pairs. Second, given a task and target language, how should one choose a source language. Third, which characteristics of a language pair are predictive of transfer performance, and how does that depend on the given task. Our empirical study with 1,808 experiments reveals practical and scientific insights, such as Kotlin and JavaScript being the most transferable source languages and different tasks relying on substantially different features. Overall, we find that learning transfers well across several programming languages., Comment: 15 pages, 9 figures, 8 tables

Code Large Language Models (Code LLMs) are being increasingly employed in real-life applications, so evaluating them is critical. While the conventional accuracy evaluates the performance of Code LLMs on a set of individual tasks, their self-consistency across different tasks is overlooked. Intuitively, a trustworthy model should be self-consistent when generating natural language specifications for its own code and generating code for its own specifications. Failure to preserve self-consistency reveals a lack of understanding of the shared semantics underlying natural language and programming language, and therefore undermines the trustworthiness of a model. In this paper, we first formally define the self-consistency of Code LLMs and then design a framework, IdentityChain, which effectively and efficiently evaluates the self-consistency and conventional accuracy of a model at the same time. We study eleven Code LLMs and show that they fail to preserve self-consistency, which is indeed a distinct aspect from conventional accuracy. Furthermore, we show that IdentityChain can be used as a model debugging tool to expose weaknesses of Code LLMs by demonstrating three major weaknesses that we identify in current models using IdentityChain. Our code is available at https://github.com/marcusm117/IdentityChain., Comment: ICLR 2024

The Near-Earth Object (NEO) Surveyor mission is a NASA observatory designed to discover and characterize near-Earth asteroids and comets. The mission's primary objective is to find the majority of objects large enough to cause severe regional impact damage ($>$140 m in effective spherical diameter) within its five-year baseline survey. Operating at the Sun-Earth L1 Lagrange point, the mission will survey to within 45 degrees of the Sun in an effort to find the objects in the most Earth-like orbits. The survey cadence is optimized to provide observational arcs long enough to reliably distinguish near-Earth objects from more distant small bodies that cannot pose an impact hazard. Over the course of its survey, NEO Surveyor will discover $\sim$200,000 - 300,000 new NEOs down to sizes as small as $\sim$10 m and thousands of comets, significantly improving our understanding of the probability of an Earth impact over the next century., Comment: accepted to PSJ

A $2$-$(v,k,\lambda)$ design is additive (or strongly additive) if it is possible to embed it in a suitable abelian group $G$ in such a way that its block set is contained in (or coincides with) the set of all the zero-sum $k$-subsets of $G$. Explicit results on the additivity or strong additivity of symmetric designs and subspace 2-designs are presented. In particular, the strong additivity of PG$_d(n,q)$, which was known to be additive only for $q=2$ or $d=n-1$, is always established.

Dynamic Light Scattering (DLS) and Small-Angle Neutron Scattering (SANS) are two key tools with which to probe the dynamic and static structure factor, respectively, in soft matter. Usually DLS and SANS measurements are performed separately, in different laboratories, on different samples and at different times. However, this methodology has particular disadvantages for a large variety of soft materials which exhibit high sensitivity to small changes in fundamental parameters such as waiting times, concentration, pH, ionic strength, etc. Here we report on a new portable DLS-SANS apparatus that allows one to simultaneously measure both the microscopic dynamics (through DLS) and the static structure (through SANS) on the same sample. The apparatus has been constructed as a collaboration between two laboratories, each an expert in one of the scattering methods, and was commissioned on the \textit{LOQ} and \textit{ZOOM} SANS instruments at the ISIS Pulsed Neutron \& Muon Source, U.K.

The combination of soft responsive particles, such as microgels, with nanoparticles (NPs) yields highly versatile complexes of great potential for applications, from ad-hoc plasmonic sensors to controlled protocols for loading and release. However, the assembly process between these microscale networks and the co-dispersed nano-objects has not been investigated so far at the microscopic level, preempting the possibility of designing such hybrid complexes a priori. In this work, we combine state-of-the-art numerical simulations with experiments, to elucidate the fundamental mechanisms taking place when microgels-NPs assembly is controlled by electrostatic interactions. We find a general behavior where, by increasing the number of interacting NPs, the microgel deswells up to a minimum size, after which a plateau behavior occurs. This occurs either when NPs are mainly adsorbed to the microgel corona via the folding of the more external chains, or when NPs penetrate inside the microgel, thereby inducing a collective reorganization of the polymer network. By varying microgel properties, such as fraction of crosslinkers or charge, as well as NPs size and charge, we further show that the microgel deswelling curves can be rescaled onto a single master curve, for both experiments and simulations, demonstrating that the process is entirely controlled by the charge of the whole microgel-NPs complex. Our results thus have a direct relevance in fundamental materials science and offer novel tools to tailor the nanofabrication of hybrid devices of technological interest.

Deep Learning (DL) models to analyze source code have shown immense promise during the past few years. More recently, self-supervised pre-training has gained traction for learning generic code representations valuable for many downstream SE tasks, such as clone and bug detection. While previous work successfully learned from different code abstractions (e.g., token, AST, graph), we argue that it is also essential to factor in how developers code day-to-day for general-purpose representation learning. On the one hand, human developers tend to write repetitive programs referencing existing code snippets from the current codebase or online resources (e.g., Stack Overflow website) rather than implementing functions from scratch; such behaviors result in a vast number of code clones. In contrast, a deviant clone by mistake might trigger malicious program behaviors. Thus, as a proxy to incorporate developers' coding behavior into the pre-training scheme, we propose to include code clones and their deviants. In particular, we propose CONCORD, a self-supervised, contrastive learning strategy to place benign clones closer in the representation space while moving deviants further apart. We show that CONCORD's clone-aware contrastive learning drastically reduces the need for expensive pre-training resources while improving the performance of downstream SE tasks. We also empirically demonstrate that CONCORD can improve existing pre-trained models to learn better representations that consequently become more efficient in both identifying semantically equivalent programs and differentiating buggy from non-buggy code., Comment: Camera-ready for 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 23)

The recent improvement in code generation capabilities due to the use of large language models has mainly benefited general purpose programming languages. Domain specific languages, such as the ones used for IT Automation, have received far less attention, despite involving many active developers and being an essential component of modern cloud platforms. This work focuses on the generation of Ansible-YAML, a widely used markup language for IT Automation. We present Ansible Wisdom, a natural-language to Ansible-YAML code generation tool, aimed at improving IT automation productivity. Ansible Wisdom is a transformer-based model, extended by training with a new dataset containing Ansible-YAML. We also develop two novel performance metrics for YAML and Ansible to capture the specific characteristics of this domain. Results show that Ansible Wisdom can accurately generate Ansible script from natural language prompts with performance comparable or better than existing state of the art code generation models. In few-shot settings we asses the impact of training with Ansible, YAML data and compare with different baselines including Codex-Davinci-002. We also show that after finetuning, our Ansible specific model (BLEU: 66.67) can outperform a much larger Codex-Davinci-002 (BLEU: 50.4) model, which was evaluated in few shot settings.

This article presents a new method for estimating the electron temperature of the Protosphera's screw pinch. The temperature radial profile is obtained by a self-consistent modeling of a 1D MHD equilibrium along with a 0D power balance of the plasma column, given measurements and estimates of the axial pinch plasma current, of the plasma rotational frequency and, at the equatorial plane, of the electron density radial profile, of the edge poloidal magnetic field, of the edge electron temperature and of the neutrals pressure in the vacuum vessel. The plasma is considered in equilibrium with its neutral phase and in constant rotation. A MATLAB code has been developed with the aim of estimating the MHD radial equilibrium profiles, the thermodynamic plasma state and the neutrals profile. The numerical estimates are compared with available experimental data showing a good agreement., Comment: 4 pages, 6 figures, 1 table, research presented to the "6th ICFDT"

We say that a linear space is harmonious if it is resolvable and admits an automorphism group acting sharply transitively on the points and transitively on the parallel classes. Generalizing old results by the first author et al. we present some difference methods to construct harmonious linear spaces. We prove, in particular, that for any finite non-singleton subset $K$ of $\mathbb{Z}^+$ there are infinitely many values of $v$ for which there exists a partitioned difference family that is the base parallel class of a harmonious linear space with $v$ points whose block sizes are precisely the elements of $K$.

While no known asteroid poses a threat to Earth for at least the next century, the catalog of near-Earth asteroids is incomplete for objects whose impacts would produce regional devastation. Several approaches have been proposed to potentially prevent an asteroid impact with Earth by deflecting or disrupting an asteroid. A test of kinetic impact technology was identified as the highest priority space mission related to asteroid mitigation. NASA's Double Asteroid Redirection Test (DART) mission is the first full-scale test of kinetic impact technology. The mission's target asteroid was Dimorphos, the secondary member of the S-type binary near-Earth asteroid (65803) Didymos. This binary asteroid system was chosen to enable ground-based telescopes to quantify the asteroid deflection caused by DART's impact. While past missions have utilized impactors to investigate the properties of small bodies those earlier missions were not intended to deflect their targets and did not achieve measurable deflections. Here we report the DART spacecraft's autonomous kinetic impact into Dimorphos and reconstruct the impact event, including the timeline leading to impact, the location and nature of the DART impact site, and the size and shape of Dimorphos. The successful impact of the DART spacecraft with Dimorphos and the resulting change in Dimorphos's orbit demonstrates that kinetic impactor technology is a viable technique to potentially defend Earth if necessary., Comment: Accepted by Nature

After extending the classic notion of a tight Heffter array H$(m,n)$ to any group of order $2mn+1$, we give direct constructions for elementary abelian tight Heffter arrays, hence in particular for prime tight Heffter arrays. If $q=2mn+1$ is a prime power, we say that an elementary abelian H$(m,n)$ is ``over $\mathbb{F}_q$" since, for its construction, we exploit both the additive and multiplicative structure of the field of order $q$. We show that in many cases a direct construction of an H$(m,n)$ over $\mathbb{F}_q$, say $A$, can be obtained very easily by imposing that $A$ has rank 1 and, possibly, a rich group of {\it multipliers}, that are elements $u$ of $\mathbb{F}_q$ such that $u A=A$ up to a permutation of rows and columns. An H$(m,n)$ over $\mathbb{F}_q$ will be said {\it optimal} if the order of its group of multipliers is the least common multiple of the odd parts of $m$ and $n$, since this is the maximum possible order for it. The main result is an explicit construction of a rank-one H$(m,n)$ -- reaching almost always the optimality -- for all admissible pairs $(m,n)$ for which there exist two distinct odd primes $p$, $p'$ dividing $m$ and $n$, respectively.

Between 2014 December 31 and 2015 March 17, the OSIRIS cameras on Rosetta documented the growth of a 140m wide and 0.5m deep depression in the Hapi region on Comet 67P/Churyumov-Gerasimenko. This shallow pit is one of several that later formed elsewhere on the comet, all in smooth terrain that primarily is the result of airfall of coma particles. We have compiled observations of this region in Hapi by the microwave instrument MIRO on Rosetta, acquired during October and November 2014. We use thermophysical and radiative transfer models in order to reproduce the MIRO observations. This allows us to place constraints on the thermal inertia, diffusivity, chemical composition, stratification, extinction coefficients, and scattering properties of the surface material, and how they evolved during the months prior to pit formation. The results are placed in context through long-term comet nucleus evolution modelling. We propose that: 1) MIRO observes signatures that are consistent with a solid-state greenhouse effect in airfall material; 2) CO2 ice is sufficiently close to the surface to have a measurable effect on MIRO antenna temperatures, and likely is responsible for the pit formation in Hapi observed by OSIRIS; 3) the pressure at the CO2 sublimation front is sufficiently strong to expel dust and water ice outwards, and to compress comet material inwards, thereby causing the near-surface compaction observed by CONSERT, SESAME, and groundbased radar, manifested as the "consolidated terrain" texture observed by OSIRIS., Comment: 32 pages, 41 figures. This is a pre-copyedited, author-produced PDF of an article accepted for publication in MNRAS following peer review

We here study the level of albedo variegation on the nucleus of Comet 67P/Churyumov-Gerasimenko. This is done by fitting the parameters of a standard photometric phase function model to disk-average radiance factor data in images acquired by the Rosetta/OSIRIS Narrow Angle Camera in the orange filter. Local discrepancies between the observed radiance factor and the disk-average solution are interpreted as a proxy W of the local single-scattering albedo. We find a wide range 0.02

Among hydrocolloids, gellan is one of the most used anionic polysaccharides, because of its capability of forming mechanically stable gels at relatively low concentrations. Despite its long-standing use and importance, the gellan aggregation mechanism is still not presently understood at the microscopic level due to the lack of atomistic information. Here we will fill this gap by reporting molecular dynamics simulations of gellan chains at different polymer and salt contents, being able to unveil the occurrence of the two steps in the process, in agreement with existing hypotheses. At first, the formation of double helices takes place, followed by the aggregation into super-structures. For both steps, the role of bivalent cations appears to be crucial, as also shown by rheology and atomic force microscopy measurements: they not only facilitate the junction of the chains into double helices, but also promote through bridging their arrangement into larger aggregates. On the other hand, monovalent cations have a much more reduced role, making it possible to form double helices only at very high salt content and not actively participating in the formation of gels. Our simulations thus offer the first complete microscopic overview of gellan aggregation and will be important for future use of gellan-based systems for a wide variety of applications, ranging from food science to art restoration.

Unmanned aerial base stations (UABSs) can be deployed in vehicular wireless networks to support applications such as extended sensing via vehicle-to-everything (V2X) services. A key problem in such systems is designing algorithms that can efficiently optimize the trajectory of the UABS in order to maximize coverage. In existing solutions, such optimization is carried out from scratch for any new traffic configuration, often by means of conventional reinforcement learning (RL). In this paper, we propose the use of continual meta-RL as a means to transfer information from previously experienced traffic configurations to new conditions, with the goal of reducing the time needed to optimize the UABS's policy. Adopting the Continual Meta Policy Search (CoMPS) strategy, we demonstrate significant efficiency gains as compared to conventional RL, as well as to naive transfer learning methods., Comment: submitted for conference publication

Poly(N-isopropylacrylamide) (PNIPAM) is a synthetic polymer that is widely studied for its thermoresponsive character. However, recent works also reported evidence of a low temperature (protein-like) dynamical transition around 225 K in concentrated PNIPAM suspensions, independently of the polymer architecture, i.e., both for linear chains and for microgels. In this work, we investigate water-polymer interactions by extensive differential scanning calorimetry (DSC) measurements of both systems, in order to understand the effect of the different topological structures on the solution behaviour, in particular regarding crystallization and melting processes. In addition, we compare protiated and deuterated microgels, in both water and deuterated water. The DSC results are complemented by dynamic light scattering experiments, which confirm that the selective isotopic substitution differently affects the solution behaviour. Our findings highlight the important role played by the polymer architecture on the solution behaviour: indeed, microgels turn out to be more efficient confining agents, able to avoid water crystallization in a wider concentration range with respect to linear chains. Altogether, the present data will be valuable to interpret future low-temperature investigations of PNIPAM dispersions, particularly by neutron scattering experiments., Comment: 33 pages, 10 figures

The phase behaviour of soft colloids has attracted great attention due to the large variety of new phenomenologies emerging from their ability to pack at very high volume fractions. Here we report rheological measurements on interpenetrated polymer network microgels composed of poly(Nisopropylacrylamide) (PNIPAM) and polyacrylic acid (PAAc) at fixed PAAc content as a function of weight concentration. We found three different rheological regimes characteristic of three different states: a Newtonian shear-thinning fluid, an attractive glass characterized by a yield stress, and a jamming state. We discuss the possible molecular mechanisms driving the formation of these states.