Our Work

Aim — to identify practical differences between AI-assisted and traditional college English teaching by examining pedagogical benefits and student learning behaviors within one comparative frame…

Aim — to identify practical differences between AI-assisted and traditional college English teaching by examining pedagogical benefits and student learning behaviors within one comparative framework. The problem arises because the balance among individualized feedback, teacher mediation, and independent practice is not maintained equally across instructional modes. Methods — a three-stage pedagogical experiment was conducted through a diagnostic pretest, formative intervention, and control posttest; the study used a quasi-experimental pretest-posttest design with 60 students in the AI-assisted teaching group and 60 students in the traditional teaching group. Internal reliability of the measurement instrument was examined with Cronbach’s alpha, while between-group outcomes were evaluated through descriptive statistics and comparative analysis. Results — the baseline achievement score was M = 60.4, SD = 8.1, with a range of 42–78; among 120 participants, 38 students, or 31.7 percent, reported regular AI-supported practice, 34 students (28.3 percent) independently reviewed textbook or lecture material, 28 students (23.3 percent) studied collaboratively with peers, and 20 students (16.7 percent) used a mixed strategy. Conclusion — structured AI-assisted teaching broadened pedagogical benefits and supported more active forms of learning behavior. The scientific contribution lies in combining instructional mode, pedagogical benefits, and behavior within a three-stage, theory-informed comparative model; practically, the findings support purposeful AI integration while retaining teacher oversight.

💥 Breaking changes Run SQL window functions over grouped rows on the aggregated rows, and evaluate QUALIFY before the projection (#29746) Type exact SQL numeric literals as Decimal and truncate SQL %…

💥 Breaking changes Run SQL window functions over grouped rows on the aggregated rows, and evaluate QUALIFY before the projection (#29746) Type exact SQL numeric literals as Decimal and truncate SQL %/DIV (#29536) Allow deterministic expression plugins to opt into CSE/CSPE (#29428) Read Parquet ENUM type as pl.String (#29331) More map operations (#29296) Deprecate cut/qcut (#29329) 🚀 Performance improvements Fix phases ending too soon due to join sampling (#29752) Group record batch fetches of remote IPC scans (#29750) Mark group-by node as memory intensive pipeline blocker (#29749) Don't inline slow OOC memory drift path (#29745) Only prefetch on unspill when there is memory headroom (#29701) Pushdown filters to scan_lance (#29538) Do not materialize equal ScalarColumns in Column::append/extend (#28989) Evaluate scalar windows in the streaming window node (#29698) Don't materialize scalar columns in DataFrame::estimated_size (#29711) Defer cached pread from prefetch to decode for Parquet (#29702) Decode IPC scans out of order when order is not observed (#29675) IPC metadata suffix fetch (#29692) Speed up null tracking in streaming group-by sum, min and max (#29691) Cache Iceberg manifest files across scans (#29623) Improve pushdown support for fallible Hive predicates (#29594) Streamline BytecodeParser method rewriting (#29632) Stream from_dicts records straight into column buffers (#29656) Read correlated SQL aggregates from the outer join when the subquery repeats it (#29685) Emit files unordered for remote IPC files when order not observed (#29678) Don't keep input order for order-insensitive windows in all engines (#29680) Fix parallelization in top-k reducer (#29684) Share one bloom filter between the build threads of a runtime filter (#29677) Add streaming (out-of-core) sort (#29657) Insert keys that start a run of equal keys into the hot group-by table right away (#29673) Prefetch key-row hash table lookups in blocks (#29663) Lower count-guarded sums to a sum that is null on empty input (#29668) Use single PUT for small cloud uploads (#29603) Don't cache plain scans in the streaming engine (#29654) Change single-key group-by hash table layout and add prefetching (#29661) Use the integer ranges of sampled parquet row groups in filter estimates (#29655) Raise HTTP rate-limiter read init default (#29584) Change join hash table layout and add prefetching (#29653) Add a fast-path for as_list with only a single input (#29592) Use one runtime filter builder per thread for a finished sample (#29646) Compute decimal addition, subtraction and multiplication in i64 when values fit (#29638) Spread decimal sums and means over lanes and check the sum's 38 digits once (#29637) Compute decimal addition, subtraction and multiplication without per-row validity (#29634) Skip or reuse UDF disassembly in BytecodeParser (#29625) Rescale a single decimal operand once in addition and subtraction (#29631) Dynamic hot table size in streaming GroupBy (#29629) Lower gathering from literal as elementwise (#29605) Execute fixed-size rolling windows on streaming engine (#29602) Use the finite rule of equi joins to determine build side of semi/anti (#29617) Drop the byte limit on runtime filter build sides (#29618) Add eviction-free path to GroupedReduction, with lanes (#29613) Improve window functions (#29591) Push down is_nan/is_not_nan filters to Iceberg (#29579) Compute shared group-by agg input subexpressions once (#29574) Emit files unordered for remote Parquet files when order not observed (#29581) Filter rows by the runtime join key range (#29576) Update few-group sums, means and counts in lanes (#29573) Loop over 4k arrays in group-by update (#29572) Decode parquet scans out of order when order is not observed (#29546) Don't always row-encode multi-column group-by (#29570) Push down str.starts_with filters to Iceberg (#29545) Trace join runtime filters through unions (#29565) Fold SQL temporal literals into plain values (#29562) Don't rehash stored key on every TotalIndexMap probe (#29561) Fuse drops into all filters on streaming engine (#29550) Join probe on Arrays directly (#29558) Better build side selection in equi-join sampler (#29524) Large optimisation for BytecodeParser rewrite/dispatch (#29548) Parallelize expressions in in-memory map fallback (#29535) Push down != filters to Iceberg (#29455) Improve predicate stats (#29495) Scale bloom filters from keys seen (#29477) Optimize simple like queries (#29459) Insert head slice below select(len() <cmp> n) to enable slice pushdown (#29209) Parallelize row encoding in the row_encode expression (#29434) Degrade outer join optimization (#29432) Optionally reorder semi join (#29443) Borrow the cached regex instead of cloning it per page (#29422) Lower SQL LIKE '%x%' to a literal substring match (#29431) Optimize is_in expression (#29425) Pushdown bloom filters in probe side (#29423) Narrow the decimal rescale to 64 bits when the value fits (#29396) Use a thread-local copy of a pushed-down regex predicate (#29411) Sample anti-join build side (#29416) Improve performance importing from arrow (#29412) Sample table size to determine build side in semi joins (#29375) Optimize row-encoding (#29405) Order pushed parquet predicate columns by measured selectivity (#29397) Coerce float literals to decimal instead of casting the column (#29395) Fix OOM on TPCH SQL and fix fuzzing errors (#29389) Restrict correlated SQL aggregates to requested keys (#29383) Prepare Parquet scans for row-group splitting in Polars Cloud (#29295) Skip row groups by join runtime ranges without a statistics frame (#29370) Reduce copy in scan_lines (#29310) Increase HTTP read rate-limit default (#29363) Evaluate a pushed parquet predicate sequentially per conjuct (#29352) Disable system certificates for CloudScheme::Http sources (#29284) Reduce rechunk in sort_in_place (#29343) Dynamic predicates for hash joins (#29312) Use HTTP suffix range for Parquet size and footer (#29308) Derive predicates from join conditions (#29304) Lower uncorrelated subqueries to semi joins and push semi/anti joins below inner joins (#29289) Make leaf name iterator unique (#29291) Don't clone the full frame per arm in when/then/otherwise (#29258) Push inner joins before outer joins and rewrite left-join-is-null to anti join (#29277) Use stats to decide cross join buffering side (#29270) Improve cache-removal and join-order cost estimates (#29263) Improve CSPE cost evaluation (#29250) Fuse group-by pre-select into node after partition (#29251) Inline hot small functions (#29244) Fix plan-time regressions in projection pushdown for wide frames (#28724) Rechunk before selecting in group-by pre-select (#29219) Reuse Iceberg data file sizes (#29063) ✨ Enhancements Python Polars 2.0 (#29723) Enable OOC by default with 80% of available RAM as threshold (#29741) Support window frames in SQL FIRST_VALUE and LAST_VALUE, and add NTH_VALUE and a LAG/LEAD default (#29740) Set default OOC disk budget to 64 GB (#29734) Add POLARS_OOMKILL_THRESHOLD_MB (#29735) Improve estimated DataFrame memory usage (#29712) Extend pipe_with_dtype for multiple expressions (#29676) Attribute physical nodes to IR nodes (#29522) Make approx_quantile sketch states mergeable across processes (#29660) Add unstable scan_lance (#29413) New Expression and function: pipe_with_dtype (#29547) Resolve is_in and Map lookup coercion from dtypes alone (#29487) Cast the needle of is_in and Map lookups exactly or not at all (#29486) Support Map in JSON and NDJSON reading and writing (#29478) Add scan_external_reader (#29232) Add struct.eval (#29454) Improve BytecodeParser UDF variable resolution (#29553) Type exact SQL numeric literals as Decimal and truncate SQL %/DIV (#29536) Make Iceberg sink commits idempotent across re-executions (#29512) Allow deterministic expression plugins to opt into CSE/CSPE (#29428) Improve cloud object_store IO error types and messages (#29471) Add erf(c) function (#29501) Update BytecodeParser for Python 3.15 (#29491) Expose the registered source as scan_fn.io_source (#28897) Support selectors in join keys (#29233) Honor Iceberg sort orders in native sinks (#29318) Add APPROX_QUANTILE to the SQL frontend (#29288) Add support for approx_quantile in the streaming engine (#29237) Read Parquet ENUM type as pl.String (#29331) Expose more scan_iceberg/delta-related attributes in the visitor for cudf_polars (#29297) More map operations (#29296) Binning functions (#28888) Support collect and collect_batches using RemoteEngine (#28914) Support GROUP BY GROUPING SETS, ROLLUP, CUBE and GROUPING() (#29278) Fix tpch SQL issues (#29269) Fuse filters in (inner) join operation (#29218) Add in-memory support for approximate quantile (#29206) Disable casts from String to Time (#29215) 🐞 Bug fixes Find SQL aggregates by their function name, and raise on nested aggregate calls (#29751) Run SQL window functions over grouped rows on the aggregated rows, and evaluate QUALIFY before the projection (#29746) Match categories added after is_in prepares a string haystack (#29744) Give tied rows the same running aggregate in SQL windows, and support more window frames (#29736) Fix scan_lance CI error (#29737) Rank NULLs and ties in SQL window functions, and add PERCENT_RANK, CUME_DIST and NTILE (#29729) Read from database without requiring SQLAlchemy asyncio extra (#29713) Don't slice the input of a select that has a window expression (#29725) Fix named SQL windows and raise for window shapes that gave wrong results (#29720) Preserve projections across nested caches (#29710) Allow the same equi-join key pair twice in a join condition (#29715) Defer fallible Hive pruning until after partition rewriting (#29700) Make dynamic window bounds data-independent (#29706) Panic on empty windows in dynamic group-by (#29704) Only reserve builder room for the rows a sort bucket receives (#29696) Fix handling of pruned input nodes during graph traversal (#29532) Minor fixes for DataFrame "orient" behaviour (#29679) Fix list.contains on multi-chunk sliced lists (#29635) Make is_sorted order nested types as sort does (#29683) Fix compile errors after attributing physical nodes to IR nodes (#29687) Raise on ragged rows instead of silently dropping values (#29658) Exclude IPC dictionary batches from record batch stats row count (#29672) Handle reordered groups in sort_by (#29639) Don't recompile regex (#29597) Fix null and mixed-dtype edge cases in is_in (#29593) Errors in str.to_lowercase and str.to_titlecase (#29607) Make str.zfill consistent with pad for unicode (#29604) Empty group-by argmin/max on scalar (#29608) Support nested by in grouped min_by/max_by in streaming engine (#29628) Guard is_nan/is_not_nan pushdown against Decimal columns in Iceberg (#29610) Fix read_excel from_arrow error (#29492) Improve default S3 endpoint resolution (#29470) Don't let a SQL derived table alias replace a registered table (#29577) Write a single Avro header when a DataFrame has multiple chunks (#29569) Fix bug in group_by predicate pushdown (#29499) Preserve literal state in list/arr eval under group_by (#29557) Don't evict when updating an existing LRUCache key (#29551) Use SQL decimal result scales for * and / (#29520) Compute mixed-scale Decimal operations without a lossy common cast (#29519) Keep Decimal results within their declared precision and round Decimal to float casts correctly (#29539) Suggest str.contains for string containment in map_elements UDFs (#25472) Keep a landed Iceberg snapshot's manifests when a commit response is lost (#29511) Allow deterministic expression plugins to opt into CSE/CSPE (#29428) Keep requested length in streaming negative slice (#29399) Match engine output dtype in planner for Decimal and integer arithmetic (#29515) Push down != filters to Iceberg (#29455) Reject non-numeric input and preserve Decimal scale in entropy (#29228) Honor env var in Parquet/IPC pipeline budget (#29518) Stop casting data to a Decimal needle in is_in, allow Array(Null) casts (#29485) Clamp inflight budget from HTTP rate-limiter (#29497) Don't propagate RUSTFLAGS into dependencies in coverage (#29510) Read legacy Parquet LIST structures according to the spec (#29469) Address Python 3.15 compatibility issue with _is_empty_method (#29489) Insert head slice below select(len() <cmp> n) to enable slice pushdown (#29209) Fix loading negative decimals from iceberg statistics (#29452) Support NaN comparison pushdown to Iceberg (#29453) Stop parse_version from splicing a pre-release suffix into the number (#29401) Produce correct parquet statistics for enum columns (#29364) Don't restart predicate pushdown if the predicate was not pushable (#29418) Add regression test for Decimal/integer arithmetic schema (#29120) Dynamic boundary schema mismatch (#29448) Avoid panic on Enum and Categorical literals in Parquet predicates (#29421) Fix SQL count star on CSV performance regression (#29427) Respect include_bounaries on in-mem empty dynamic (#29440) Fix over ordering for multiple cols (#29417) Enable dtype-i128 alongside dtype-decimal in polars-stream (#29410) Prevent bias in 'req_double' at the median by actually merging the sketches (#29326) Fix OOM on TPCH SQL and fix fuzzing errors (#29389) Size row-index table statistics from the statistics frame (#29381) Preserve categories object in pyo3-polars (#29385) Strip the leading slash from Windows Delta table roots (#29386) Isolate expanded Python dataset scans (#29378) Make Iceberg bucket sort keys serializable (#29376) Apply "schema_overrides" in read_database for Arrow-based drivers (#29273) Remove duplicated word in rate-limit comment (#29372) Check whether Datetime is monotonically increasing dynamically (#29293) Keep input order of unmatched build rows in ordered streaming equi join (#29371) Unaliased constants in SQL SELECT with GROUP BY (#29367) Consistent Date and Decimal means between the streaming and in-memory engines (#29359) Respect string statistics for enum columns during parquet scanning (#29366) Support selectors properly in DataFrame n_unique (#29360) Decimal Parquet statistics for decimal/i128/f16 (#29350) Early check for converting integer map keys (#29348) Lowering for input-independent filter (#29340) Correlation of constant column returning non-NaN for larger inputs (#29319) Incorrect height in multi-input GroupBy (#29332) Fix panic in scan_iceberg for snapshot_id before a schema change (#28895) Resolve arithmetic Struct supertypes per-field (#29261) Fix comparison expression method comment (#29257) Don't panic on an empty or null quantile expression input (#29240) Detect list-valued quantile literals in approx_quantile auto (#29236) Various map issues (#29147) Rolling quantile should respect window trimming (#29200) Ensure ignored columns are excluded from dtype Wildcard selector (#29220) 📖 Documentation Add engines and other missing items to API reference (#29493) Update migration guide with rc2 changes (#29415) Clarify that ambiguous parameter refers to DST transitions (#28873) Document gzip/zstd compression for read_csv and scan_csv (#29387) Add LazyFrameResolver to reference guide (#29379) Add user-guide for new enable_monitoring feature (#29358) Improve join_where engine tag (#29234) 🛠️ Other improvements Hold the category mapping in the categorical is_in lookup (#29747) Derive serde for moment states (#29742) Give each crate its own temporary column name counter (#29689) Apply A-io-partitioning label for Hive-related issues and PRs (#29659) Use explicit match arms in LogSeries operations & improve error messages (#29575) Improve reliability of a slightly flaky test (#29587) Split has_joins_or_unions into has_joins and has_unions (#29338) Remove scheduled cache cleaning (#29517) Add window placement to group by rolling (#29529) Add window placement to group by dynamic (#29527) Fix flaky test (#29530) Improve cloud object_store IO error types and messages (#29471) Fix iceberg-related test failures (#29533) Add IR structs for temporal group-by options (#29526) Workflow tweaks (#29502) Share the temporal group-by index space (#29498) Compute the first dynamic window start in one place (#29484) Fix anti/semi join test row with invalid result order expectation (#29467) Additional negative Decimal coverage for Iceberg (#29468) Add regression test for Decimal/integer arithmetic schema (#29120) Tidy the staged parquet predicate (#29408) Add dymanicpredicates to preferred build sides (#29335) Deprecate cut/qcut (#29329) Mark test as slow (#29336) Bump maturin (#29282) Bump object_store crate to 0.14.2 (#29317) Update rustls dependency to version 0.23.45 (#29303) Bump build deps used in ARM64 Windows release pipeline (#29280) Fix the stalling test_fused_many_morsels_and_skew test (#29290) Use SpillFrames in DataFrameSearchBuffers (#29207) More obvious MapChunked storage handling (#29248) Centralize hoisted aggregate bookkeeping and clarify grouping predicates (#29287) Update analytics endpoint config (#29222) Add a blanket lf.collect().schema == lf.collect_schema() check (#29224) Add expand_paths parameter to toggle path expansion (#29210) Thank you to all our contributors for making this release possible! @ATL2001, @Aidavdw, @AlessandroKuz, @JakubValtar, @Kevin-Patyk, @MarcoGorelli, @Punisheroot, @Rodrigo-Palma, @SatvikMishra08, @TNieuwdorp, @aarushkandukoori, @abokhalill, @alexander-beedie, @atharva7905k, @ayushh0110, @borchero, @c-peters, @cBournhonesque, @carnarez, @dancsi, @dominikandreasseitz, @dsprenkels, @fsimkovic, @gautamvarmadatla, @hadrian-reppas, @jonasdedden, @kafka1991, @kdn36, @krithikashreeL, @lun3x, @madsbk, @matthewbayer, @mikhail5555, @mroeschke, @nameexhaustion, @orlp, @r-brink, @ritchie46, @shaneraphel, @vgvr0 and @wtn

O carcinoma de células escamosas (CCE) é uma das neoplasias epiteliais malignas mais frequentes e relevantes na rotina clínica de aves de companhia e de vida livre. Caracterizado …

O carcinoma de células escamosas (CCE) é uma das neoplasias epiteliais malignas mais frequentes e relevantes na rotina clínica de aves de companhia e de vida livre. Caracterizado pela proliferação anaplásica de queratinócitos e por elevado poder de invasão tecidual local, acomete com maior frequência a pele, a glândula uropigial, junções mucocutâneas faciais, o bico e o trato gastrointestinal rostral. A etiologia envolve múltiplos fatores, destacando-se processos inflamatórios crônicos, traumas mecânicos e deficiências nutricionais como a hipovitaminose A. O diagnóstico baseia-se na correlação de exames de imagem, citologia, histopatologia e imuno-histoquímica para confirmação de linhagem epitelial (pancitoqueratinas). No âmbito terapêutico, a ressecção cirúrgica com margens livres constitui a intervenção de escolha para o controle da doença e o aumento da sobrevida. As modalidades adjuvantes, como radioterapia e quimioterapia, apresentam eficácia limitada e taxas variáveis de resposta devido à radiorresistência tumoral e toxicidade aos fármacos. A intervenção precoce permanece essencial para o prognóstico e manejo do bem-estar dos pacientes.

A Pipeline for Large-Scale Archaeological Site Detection: Integrating Remote Sensing Data with Historical Maps This repository contains data supporting the paperAlbrecht, R. (2027). A Pipeline for&nbs…

A Pipeline for Large-Scale Archaeological Site Detection: Integrating Remote Sensing Data with Historical Maps This repository contains data supporting the paperAlbrecht, R. (2027). A Pipeline for Large-Scale Archaeological Site Detection: Integrating Remote Sensing Data with Historical Maps. In: Dimitri, G.M., Aslan, S., Montanelli, S., Ravanelli, M., Subakan, C., Trentin, E. (eds) Artificial Neural Networks in Pattern Recognition. ANNPR 2026. Lecture Notes in Computer Science(), vol 16978. Springer, Cham. https://doi.org/10.1007/978-3-032-39028-8_34 Each .zip folder contains the labelled data separated by region: Khabur.zip Iraq.zip Uzbekistan.zip The images in Khabur.zip are taken from Vadineanu et al. (2023) and are under a CC-BY-SA 4.0 license.For the images in Iraq.zip and Uzbekistan.zip the tiles are taken from the Corona atlas project around labels provided by Casini et al. (2023) and they are also under the CC-BY-SA 4.0 license. All maps used from the Perry Castañeda library are in the maps.zip file.The maps are licensed as CC0, courtesy of the University of Texas Libraries, The University of Texas at Austin. References Casana, J., Cothren, J.: The corona atlas project: Orthorectification of corona satellite imagery and regional-scale archaeological exploration in the near east. In: Mapping archaeological landscapes from space, pp. 33–43. Springer (2012)Casini, L., Marchetti, N., Montanucci, A., Orrù, V., Roccetti, M.: A human–ai collaboration workflow for archaeological sites detection. Scientific Reports 13(1), 8699 (2023)Vadineanu, S., Kalayci, T., Pelt, D.M., Batenburg, K.J.: Convolutional neural networks and their activations: An exploratory case study on mounded settlements. Journal of Computer Applications in Archaeology 7(1) (2024)

This dataset is a resource developed to support research on linguistic diversity. Quantitative research in the field is limited by the lack of openly available spatiotemporal data on speaker numbers. …

This dataset is a resource developed to support research on linguistic diversity. Quantitative research in the field is limited by the lack of openly available spatiotemporal data on speaker numbers. While most such data would stem from either 1) national censuses or 2) estimates, Finland offers an exceptional possibility of studying linguistic diversity through its Population Information system, which records, among other data, the address and native language of any person residing in Finland. The speaker data is published by Statistics Finland (CC BY 4.0), and for each year from 1990 to 2024, we collected the number of native languages and their speakers registered in each municipality. As per statistic Finland, the data of a given year corresponds to the 31 december of that year.   We structured and joined the data into a single CSV: speakers_time_series_municipality.csv.We aggregated the speaker numbers across all municipalities to yield a national time series of L1-speaker statistics: speakers_time_series_finland.csv. Furthermore, we provide three time series with pre-computed diversity measures according to the Leinster-Cobbold framework. One for each municipality: diversity_time_series_municipality.csv, one for each region: diversity_region_time_series.csv  one for Finland as a whole: diversity_finland_time_series.csv,  The data can be explored interactively at GitHub pages: or as a shiny app. The code is available at: https://github.com/Eszettfors/FinLingDiv This research was funded by WWTF (grant number ICT23-012). It is a part of the DIGILINGDIV-project.Changelog:- V1.1: updated with data from 2025.- V1.1.1: added regional timeseries on speaker numbers and diversity indices. 

This study aimed to evaluate the treatment performance of constructed wetland (CW) systems using alternative sustainable substrates derived from cork as filter media. Four lab-scale CW units were…

This study aimed to evaluate the treatment performance of constructed wetland (CW) systems using alternative sustainable substrates derived from cork as filter media. Four lab-scale CW units were operated using raw cork, expanded cork, gravel enriched with biochar-based cork, and gravel as substrate materials. The effects of substrate type on organic matter removal, nitrogen transformation, micropollutant attenuation, plant development, and microbial community composition were investigated. Results showed significant differences among substrates for chemical oxygen demand (COD) and nitrate nitrogen (NO₃⁻–N) removal (ANOVA test, p < 0.05). Expanded cork showed more consistent COD removal performance, with lower variability, while cork-based substrates showed enhanced nitrate removal compared with conventional gravel-based systems. These results suggest that cork substrates may provide favorable physicochemical conditions for microbial processes involved in nitrogen transformation. For bisphenol A (BPA), raw and expanded cork achieved high removal rates >90% under the applied experimental loading conditions. Cork based-substrates also provided favorable conditions for plant growth, especially in horizontal flow constructed wetlands (HFCWs). Shotgun metagenomic sequencing revealed that microbial communities were dominated by bacterial taxa across all configurations, with Pseudomonadota being the most abundant (60–80%), followed by Actinomycetota, Bacteroidota, and Bacillota.Fungal taxa were detected only in the HFCW with raw cork (HFCW2). Overall, the findings highlight the potential of cork-based substrates as sustainable filter media for CW applications.

This software archive contains the R scripts and input files used for the GSE132714 differential-expression analyses, transcriptomic candidate-overlap analyses, and GO/KEGG functional-enrichment analy…

This software archive contains the R scripts and input files used for the GSE132714 differential-expression analyses, transcriptomic candidate-overlap analyses, and GO/KEGG functional-enrichment analyses reported in the manuscript “Distinct Cellular Responses of BPH-1 Cells to Daidzein and Puerarin: An Integrative Computational and In Vitro Study”. The archive includes the primary library-type-adjusted DESeq2 model, the Poly-A-only sensitivity analysis, the exploratory unadjusted full-sample model, candidate-set overlap analyses, functional-enrichment scripts, archived session information, and key expected outputs for reproducibility checks. The public RNA-sequencing dataset analysed is GSE132714. Detailed file descriptions, software versions, and execution instructions are provided in README.md.

Solid-state batteries (SSBs) offer higher energy densities, improved safety from non-flammable solid electrolytes, and longer lifespans compared to traditional lithium-ion batteries. However, modeling…

Solid-state batteries (SSBs) offer higher energy densities, improved safety from non-flammable solid electrolytes, and longer lifespans compared to traditional lithium-ion batteries. However, modeling SSBs presents unique challenges due to their distinct electrical and thermal behaviors. This study presents an experimental characterization and electro-thermal model for a next-generation 30 Ah polymer-based SSBs. This work integrates experimental characterization, electrical modeling using a third-order equivalent circuit, and thermal modeling with a lumped thermal mass to represent temperature dynamics. Through comprehensive testing, including open-circuit voltage and hybrid pulse power characterization, we identified dependencies of key parameters on state of charge and temperature. Two-way coupling is used between the electrical and thermal models, where the first feeds the second one with the heat generated while the thermal model provides the temperature to update electrical parameters accordingly. This approach accounts for both irreversible heat from internal resistance and reversible heat from entropy changes, determined through a validated method correlating open-circuit voltage and temperature. Results demonstrate that the proposed model can simulate the dynamic interactions between the electric and thermal behavior of a SSB and predicts the electric performance as well as the cell surface temperature with high accuracy.

Female fertility and ovarian function are controlled by a complex network of hormonal signals, in which estrogen receptors play an important regulatory role. Among these receptors, estrogen receptor 1…

Female fertility and ovarian function are controlled by a complex network of hormonal signals, in which estrogen receptors play an important regulatory role. Among these receptors, estrogen receptor 1 (ESR1) is widely expressed in ovarian tissues and contributes to essential reproductive processes, including ovulation and maintenance of hormonal balance. In recent years, natural phytochemicals have attracted attention as potential regulators of estrogen receptor activity because they possess structures similar to natural estrogens and generally show good safety profiles. In this study, potential phytochemical candidates were evaluated for their ability to interact with estrogen receptor 1 (ESR1; UniProt ID: P03372; PDB ID: 1A52), using Estradiol as a standard reference compound. Molecular docking analysis was carried out using LibDock and CDOCKER protocols available in BIOVIA Discovery Studio 2019. In addition, structural dynamics studies were performed to assess the stability and behavior of protein-ligand complexes. The docking results showed that the selected phytochemicals demonstrated strong binding potential toward ESR1 by forming interactions with important amino acid residues within the receptor's ligand-binding region. When compared with the reference compound Estradiol, these compounds showed favorable binding patterns and stable conformations. Further structural dynamics analysis supported the stability of the formed complexes. Overall, the findings indicate that the investigated phytochemical, Epicatechin Gallate (PubChem CID: 107905), may have the potential to influence ESR1-related signaling pathways involved in female reproductive health and ovarian physiology. This computational study provides valuable preliminary evidence for further experimental research toward the development of plant-based therapeutic approaches for reproductive health management.

“Parlare dialetto in Italia alle soglie del Duemila”, in Beccaria, Gian Luigi/Marello, Carla (a cura di), La parola al testo. Scritti per Bice Mortara Garavelli, 2 voll., Alessandria, Ediz…

“Parlare dialetto in Italia alle soglie del Duemila”, in Beccaria, Gian Luigi/Marello, Carla (a cura di), La parola al testo. Scritti per Bice Mortara Garavelli, 2 voll., Alessandria, Edizioni dell’Orso, [2001], pp. 33-49.