Our Work

The rapid deployment of Generative Artificial Intelligence (GenAI) across enterprise environments represents a foundational shift in how work is structured, cognitive tasks are allocated, and individu…

The rapid deployment of Generative Artificial Intelligence (GenAI) across enterprise environments represents a foundational shift in how work is structured, cognitive tasks are allocated, and individual productivity is realized. This critical review systematically synthesizes empirical and conceptual literature published between 2021 and 2026 to examine the multi-dimensional impact of GenAI on employee productivity and job redesign. Guided by Job Demands-Resources (JD-R) theory, Socio-Technical Systems (STS) theory, and the Task-Technology Fit (TTF) framework, this paper analyzes findings across 16 benchmark studies encompassing randomized field experiments, structural equation modeling, and qualitative case investigations. Results indicate that GenAI integration yields significant task-level productivity gains—ranging from 14% to 40% across professional domains—predominantly by automating routine cognitive tasks, reducing time-to-completion, and elevating output quality for lower-skilled workers. However, operationalizing these productivity gains requires comprehensive job redesign, characterized by cognitive task unbundling, skill reallocation toward prompt engineering and critical evaluation, and the mitigation of emerging techno-stressors. The review synthesizes core mechanisms into a structural path model and outlines a strategic HR governance framework to optimize human-AI collaboration.

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Abstract. This thesis considers SWOT and PEST analyses as complementary planning tools for dental clinics. SWOT reveals internal strengths and weaknesses and external opportunities and threats, while …

Abstract. This thesis considers SWOT and PEST analyses as complementary planning tools for dental clinics. SWOT reveals internal strengths and weaknesses and external opportunities and threats, while PEST organizes macro-environmental factors. Their joint application can support realistic service development, responsible communication, and periodic strategic review.

Tarihî metinler üzerine yapılan çalışmaların çoğu metinlerin dil özellikleri üzerine yoğunlaşmaktadır. Bu eserlerin içeriği ve tasavvufî yönü …

Tarihî metinler üzerine yapılan çalışmaların çoğu metinlerin dil özellikleri üzerine yoğunlaşmaktadır. Bu eserlerin içeriği ve tasavvufî yönü çoğu zaman ikinci planda kalmaktadır. Bunlardan biri de Berlin Devlet Kütüphanesi Osmanlı Türkçesi yazmaları koleksiyonunda Ms. or. oct. 2154 numarasıyla kayıtlı ve katalogda İlâhî-nâme başlığıyla yer alan yazma eserdir. Eserin müstensihi, telif ve istinsah tarihine ait herhangi bir kayıt bulunmamıştır. Yazma önce çeviri yazıya aktarılmış, nokta sembolüne ilişkin ifadeler belirlenmiştir. Elde edilen veriler içerik analiziyle incelenerek varlık, bilgi ve insan olmak üzere üç ana tema altında değerlendirilmiştir. Bulgular, noktanın varlığın ilk özü, ilk sebebi ve birlik ilkesi olarak çokluğun kaynağını temsil eden temel bir merkez niteliği taşıdığını göstermiştir. Nokta yalnızca vahdet, harflerin kaynağı, süveydâ, nûr ve tecelli gibi tasavvufî anlamların ötesinde farklı anlam alanlarıyla ele alınmıştır. Nokta eserde insan bedeni, yedi gezegen sistemi, on yedi kuvvet tasnifi ve harf düzeniyle bağlantı kurularak insan ile âlem arasındaki bağı açıklayan bütüncül bir anlayış içinde değerlendirilmiştir. Bu yönüyle yazma, nokta kavramını insan bedeni–gezegen–harf ilişkileri üzerinden düzenli biçimde açıklaması bakımından benzer tasavvufî metinlerden ayrılmaktadır. Çalışma, nokta sembolünün varlık, bilgi ve insan arasındaki ilişkiyi açıklayan temel ilke olarak işlev gördüğünü ortaya koymaktadır.  

Sphagneticola trilobata (L.) J.F. belongs to family Asteraceae. The presence of phytochemical compounds in the leaves of S. trilobata was evaluated using the standard procedure in methanol, acetone, e…

Sphagneticola trilobata (L.) J.F. belongs to family Asteraceae. The presence of phytochemical compounds in the leaves of S. trilobata was evaluated using the standard procedure in methanol, acetone, ethanol and water extracts. Methanolic leaf extract of S. trilobata were analyzed for the presence of different volatile compounds by Gas chromatography-Mass spectroscopy (GC-MS) technique. There are about 14 different phytochemical constituents were identified through GC-MS analysis. The methanolic extract from S. trilobata leaves with the concentrations of 50, 75, and 100 µM were assessed for their effects against Staphylococcus aureus, Staphylococcus epidermidis, Vibrio cholera and Escherichia coli. Both gram positive and negative bacteria produced their zone of inhibition at moderate level against S. trilobata methanolic leaf extracts. published by the International Journal of Biosciences | IJB  

For each fixed 1/2 < theta < 1, a uniformly shifted mollified second-moment formula is derived on windows of length T^theta with 0 < nu < min(1/2, 2theta-1, (5theta-2)/6). An exact shifted…

For each fixed 1/2 < theta < 1, a uniformly shifted mollified second-moment formula is derived on windows of length T^theta with 0 < nu < min(1/2, 2theta-1, (5theta-2)/6). An exact shifted composite divisor transformation gives a common Mellin multiplier and the rational frequencies log(pq/n). Grouping repeated frequencies with their full collision multiplicities permits elementary mean-square bounds, independently derived by Gaussian Schur and direct interval-Gram arguments. Weighted Cauchy-Schwarz gives the relative errors TM/H^2 and TM^3/H^(5/2). Both transformed residues, complex shifts, arbitrary fixed operator polynomials, unbalanced blocks, gcd sums, infinite dual tails and narrower compact-window smoothing are retained. The complementary attributed Bettin-Chandee trilinear range nu < min(1/2, (17/33)(2theta-1)) remains available.Localized counting, the unchanged certified degree-201 detector and Wang's recent pair-correlation preprint give a positive asymptotic proportion of simple critical-line zeros in (T,T+T^theta] for every fixed theta in [0.527,1). At theta=0.527 the independently certified lower density exceeds 0.0005947542001. The proof has undergone internal review, uses attributed inputs and supplies no effective starting height, external peer-review claim, worldwide-priority assertion or proof of the Riemann hypothesis.Supporting certificates, code and research artifacts are published separately at 10.5281/zenodo.23135354. This manuscript record contains only the unchanged manuscript PDF.

Patient data privacy of optically pumped magnetoencephalography for functional brain imaging is a growing concern in scientific communities and healthcare practitioners. While prior research has ident…

Patient data privacy of optically pumped magnetoencephalography for functional brain imaging is a growing concern in scientific communities and healthcare practitioners. While prior research has identified the existence of dataset dispersion and widespread metadata omissions across public repositories, the academia and industry also face critical challenges on the strict privacy regulations governing human health data. Unlike previous census efforts that merely documented these standardization gaps, this work presents a functional solution by introducing a comprehensively harmonized data catalogue and technical corpus. To ensure strict compliance with modern data protection regulations, our architecture fundamentally separates technical validation data from sensitive human recordings. We provide a unified technical corpus containing exclusively empty room recordings and inactive source runs, which are fully standardized using consistent channel naming and uniform quality control measures. Furthermore, we provide a custom data loading tool that seamlessly applies these harmonized naming conventions and metadata parameters to the local dataset copies. By bridging existing metadata gaps and enforcing patient privacy by design, our work provides a compliant and practical framework to support robust technical comparisons across diverse optically pumped magnetoencephalography architectures.

Detectability of orangutan nests at satellite resolution (Pleiades Neo, 30 cm) - simulation code and results - sim.py: sensor degradation model (Gaussian optics + detector integration, MTF ~0.15 at Ny…

Detectability of orangutan nests at satellite resolution (Pleiades Neo, 30 cm) - simulation code and results - sim.py: sensor degradation model (Gaussian optics + detector integration, MTF ~0.15 at Nyquist; 1 % noise;  products: colour, panchromatic, pansharpened 30 cm / 1.2 m)- expB2.py: paired implant design (32 real nests rescaled to 0.8-1.3 m and inserted into nest-free canopy chips  from the PeerJ "Without_nest" frames; the same chip without the nest is the control)    BLEND=alpha|poisson python3 expB2.py frozen   -> frozen ResNet50 features + logistic regression    BLEND=alpha|poisson python3 expB2.py cnn      -> small CNN trained at satellite pixel size  Five-fold cross-validation grouped by nest; AUC with 95 % bootstrap CI over nests; recall at 5 % and 1 % false-positive rate.- nestloc.json: centre and diameter (px) of each nest in the "nests pictures" folder- res_*.json: results- make_figure2.py: Figure 2 (AUC versus resolution)- make_figure3.py: Figure 3 (dedicated network AUC, nests found vs false-alarm rate, individuals relocated)Assumption: native GSD 3.5 cm (Canon S100, f = 5.2 mm, ~100 m above the canopy). Additional analyses (from nests to individuals)- run_strict.py: recall at strict false-alarm rates (21 000 held-out nest-free chips) -> res_strict.json- reg_test.py + run_twodate.py: co-registration of consecutive frames and two-date change detection -> res_twodate.json- sim_spatial.py, sim_lift.py: forest blocks of 1 km2, nests along travel paths, block flagging -> res_spatial*.json, res_lift.json Published detector and Grad-CAM (Sections 3.1 and 3.2)- detect.py, detect_sizes.py: detector of Wich et al. (2025) applied to the PeerJ frames (tiles, and whole frames at 640/1280/1920 px) -> dets_native.json, dets_sizes.json- tm.py: template matching of the 32 close-up nest photographs against the drone frames -> tm.json- gradcam.py: retrains the dedicated CNN on the same chips and computes Grad-CAM maps on held-out nests -> gradcam_chips.csv, gradcam_examples.npy (not included, regenerated by the script)- make_figure_gradcam.py: Figure 2 (Grad-CAM); make_figure2.py now draws Figure 3 and make_figure3.py Figure 4 Statistical analyses (R)- export_for_R.py: writes the per-chip CSV files used by R- stats_R/analysis.R: all statistical tests (pROC: AUC with DeLong CI; lme4: mixed-effects logistic regression, odds ratios;  Wilcoxon, Fisher, McNemar and binomial tests). Open stats_R/nest_stats.Rproj in RStudio and run source("analysis.R").  Output: stats_R/results_R.txt (R 4.3.3, pROC 1.18.5, lme4 1.1.35.1). Sensitivity to sensor sharpness (Section 4.2)- sim.py now reads SIGMA_K (default 0.542, MTF at Nyquist ~0.15; 0.391 gives ~0.30)- SIGMA_K=0.391 BLEND=mtf30 python3 mtf_sensitivity.py -> res_B2_cnn_mtf30.json

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