We explore a lightweight framework that adapts frozen large language models to analyze longitudinal clinical data. The approach integrates patient history and context within the language model space to generate accurate forecasts without model fine-tuning. Applied to neuropsychological assessments, it achieves accurate and reliable performance even with minimal training data, showing promise for early-stage Alzheimer's monitoring.
ABSTRACT Halide‐based double perovskites are appealing choices for optoelectronic devices due to their adjustable energy gaps and enhanced structural stability compared to conventional perovskites. They are also strong candidates for efficient energy conversion systems due to their remarkable thermoelectric properties. In the present study, we used first‐principles calculations and extensively examined the structural, electronic, optical, and transport features of cubic‐phase Cs 2 InAgX 6 (X = Cl, F) double perovskites. The TB‐mBJ potential revealed semiconducting nature with direct band gaps of 2.53 eV for Cs 2 InAgCl 6 and 4.39 eV for Cs 2 InAgF 6 , respectively. Additionally, the optical response is studied to evaluate its possibilities in devices used in optoelectronics. Significant absorption exists in the ultraviolet range with the vital absorption peaks noticed between 8.0 and 13.0 eV. At 50 K, the ZT values were reported to be 0.99 for both materials. This study reveals that these materials are excellent choices for next‐generation functional devices because of their remarkable optoelectronic and thermoelectric qualities.
Abdul Haseeb Hassan Khan, Aqib Ali Khan, Amjad Farid
Abstract In recent years, Perovskite solar cells (PSC) have showed promising results to substitute traditional PV technologies due to impressive power conversion efficiency (PCE) and cost-effective production. This study investigates the impact of introducing a Cs4CuSb2Cl12 (CCSC) perovskite quantum dot (PQD) interface layer among active layer and hole transport layer (HTL) in CsGeI3 as well as MAGeI3-based PSCs. It aims in enhancing the function of interface layer (IL) by improving PCE while reducing interface losses. TiO2 and Spiro-OMeTAD were employed as the electron transport layer (ETL) and HTL, respectively. SCAPS-1D software was utilized for simulating JSC, VOC, FF, and PCE of various configurations, including passivated and non-passivated structures. The results revealed a substantial increase in JSC from 13.22 mA cm−2 to 15.5 mA cm−2 and PCE from 11.67% to 14.81% for MAGeI3-based PSCs with incorporated PQD layer. Additionally, the fill factor (FF) improved from 50.55% to 76.90%. However, a decrease in VOC from 1.7 V towards 1.24 V was noticed, this was associated with the formation of an energy barrier at HTL/ absorber. For CsGeI3-based devices, a slight improvement in JSC was observed from 21.0 mA cm−2 to 21.8 mA cm−2, whereas VOC remained constant at 1.24 V. The PCE increased from 22.50% to 23.09%, but the FF decreased from 86.83% to 85.48%. However the decrease in the fill factor (FF) may be attributable to a rise in the cell series resistance due to the additional interface, which could impede charge transport and extraction. This simulation study demonstrates that the incorporation of a CCSC PQD IL among active layer / HTL can enhance the PCE and short circuit current of CsGeI3 and MAGeI3-based PSCs, providing a promising avenue for future optimizations and advancements in PSC technologies.
This paper provides different approaches for a binary sentiment classification on a small training dataset. LLMs that provided state-of-the-art results in sentiment analysis and similar domains are being used, such as BERT, RoBERTa and XLNet.
In this demo paper we present OmniLingo, an architecture for distributing data for listening- and speaking-based language learning applications and a demonstration client built using the architecture. The architecture is based on the Interplanetary Filesystem (IPFS) and puts at the forefront user sovereignty over data.
We present the ELITR ECA corpus, a multilingual corpus derived from publications of the European Court of Auditors. We use automatic translation together with Bleualign to identify parallel sentence pairs in all 506 translation directions. The result is a corpus comprising 264k document pairs and 41.9M sentence pairs.
Promising 2D Cs4In3/2Sb3/2I10and Cs4In3/2Sb3/2Cl10/Cs2Cu1/2Bi1/2Cl4lead-free halide double perovskites have suitable direct bandgaps, and ultrahigh optical absorption and carrier mobility.
This paper discusses two existing approaches to the correlation analysis between automatic evaluation metrics and human scores in the area of natural language generation. Our experiments show that depending on the usage of a system- or sentence-level correlation analysis, correlation results between automatic scores and human judgments are inconsistent.
In this paper, we present an approach to exploit phrase tables generated by statistical machine translation in order to map French discourse connectives to discourse relations. Using this approach, we created ConcoLeDisCo, a lexicon of French discourse connectives and their PDTB relations. When evaluated against LEXCONN, ConcoLeDisCo achieves a recall of 0.81 and an Average Precision of 0.68 for the Concession and Condition relations.
In this article we study verbal expression of aggression and its detection using machine learning and neural networks methods. We test our results using our corpora of messages from anonymous imageboards. We also compare Random forest classifier with convolutional neural network for "Movie reviews with one sentence per review" corpus.
Argumentation mining from social media content has attracted increasing attention. The task is both challenging and rewarding. The informal nature of user-generated content makes the task dauntingly difficult. On the other hand, the insights that could be gained by a large-scale analysis of social media argumentation make it a very worthwhile task. In this position paper I discuss the motivation for social media argumentation mining, as well as the tasks and challenges involved.
We propose two methods of learning vector representations of words and phrases that each combine sentence context with structural features extracted from dependency trees. Using several variations of neural network classifier, we show that these combined methods lead to improved performance when used as input features for supervised term-matching.
AbstractChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
International standards for lexicon formats are in preparation. To a certain extent, the proposed formats converge with prior results of standardization projects. However, their adequacy for (i) lexicon management and (ii) lexicon-driven applications have been little debated in the past, nor are they as a part of the present standardization effort. We examine these issues. IGM has developed XML formats compatible with the emerging international standards, and we report experimental results on large-coverage lexica.
AbstractThe enthalpies of mixing (ΔHM) of the following binary fused‐salt mixtures have been determined calorimetrically: ZnCl2CsCl, ZnCl2LiCl, ZnCl2AgCl, ZnBr2CsBr, ZnBr2LiBr at 665°C; ZnCl2CsCl, ZnCl2AgCl, and ZnCl2ZnBr2 at 495°C. The results are discussed with respect to the following points: (1) Comparison with the transition metal chloride‐alkali chloride systems, (2) “complexing” in the mixture. (3) effect of the network‐like structure of pure ZnX2, and (4) effect of temperature.
The complexity of a particular term-rewrite system is considered: the rule of associativity (x*y)*z --> x*(y*z). Algorithms and exact calculations are given for the longest and shortest sequences of applications of --> that result in normal form (NF). The shortest NF sequence for a term x is always n-drm(x), where n is the number of occurrences of * in x and drm(x) is the depth of the rightmost leaf of x. The longest NF sequence for any term is of length n(n-1)/2.
A quantitative representation of discourse structure can be computed by measuring lexical cohesion relations among adjacent blocks of text. These representations have been proposed to deal with sub-topic text segmentation. In a parallel corpus, similar representations can be derived for versions of a text in various languages. These can be used for parallel segmentation and as an alternative measure of text-translation similarity.
We describe the design of Comlex Syntax, a computational lexicon providing detailed syntactic information for approximately 38,000 English headwords. We consider the types of errors which arise in creating such a lexicon, and how such errors can be measured and controlled.