Government Sadiq College Women University

High-stakes examinations exert a powerful influence on classroom instruction, particularly in developing-country contexts where public assessments dominate educational culture. This qualitative case study investigates the washback effect of the Secondary School Certificate (SSC) examinations administered by the Board of Intermediate and Secondary Education (BISE), Sargodha, on the pedagogical practices of secondary school teachers. Data were gathered through semi-structured interviews with five teachers and six students from a government high school in District Sargodha and through the systematic analysis of five years of SSC examination papers using Bloom's Taxonomy revised framework. Findings reveal that between 88% and 92% of examination questions target only the knowledge (recall) level of Bloom's Taxonomy, with negligible representation of higher-order thinking skills (HOTS) such as analysis, synthesis, or evaluation. Consequently, teachers adopt examination-oriented pedagogical methods centred on rote memorisation, repeated practice of past papers, and guidebook dependency, all of which foreclose meaningful language development. Students similarly prioritise memorised answers over communicative competence. The study concludes that the SSC examination generates strong negative washback and recommends systemic assessment reform encompassing formative assessment, performance-based tasks, and higher-order thinking questions to restore pedagogical quality and promote positive washback.

This research is designed to check the relationship of Use of Facebook, Student Engagement and Student Retention. Use of Facebook is dealt as independent variables Student Engagement as mediating variable and Student Retention as dependent variable. This is quantitative research. Data is collected 600 respondents with the help of structured questionnaire. Multistage sampling techniques i.e. simple random sampling and Judgment sampling are used for selection of respondents. Results indicate that for direct relationship, Use of Facebook has significant positive impact on Student Engagement and Student Retention respectively. While, Student Engagement is partially mediating the relationship of Use of Facebook with Student Retention. In future, these kinds of researches may also conduct on different sectors like textile sector, telecommunication sector, and health sector. In future, more universities of heterogonous cities will also include for generalization of results.

This study employs density functional theory (DFT) and time-dependent DFT (TD-DFT) to design and evaluate eight novel non-fullerene acceptors (NFAs) (G1-G8) for organic solar cells (OSCs). The molecules were engineered through strategic terminal group modification of a reference indacenodithiophene (IDT)-benzothidiazole (BT) based structure. All designed systems exhibit substantially reduced bandgaps (1.73-2.00eV) and redshifted absorption profiles (λmax = 688-803nm) compared to the reference molecule (REF), leading to enhanced light-harvesting capabilities (LHE = 0.988-0.998). Marcus charge transfer theory calculations revealed high hole hopping rates (Kh ≈ 10¹⁵ s⁻¹) and low reorganization energies (λh = 0.0031-0.0052eV), indicating excellent charge transport properties. The comprehensive computational analysis projects outstanding photovoltaic performance with open-circuit voltage (VOC = 1.13-1.66V), fill factor (FF = 0.8927-0.9205), and estimated power conversion efficiency (PCE = 22.8-37.0%) across the series. Among the designed systems, G7 demonstrates exceptional promise due to its optimal bandgap (1.73eV), outstanding light-harvesting efficiency (LHE = 0.998), and the highest estimated short-circuit current (JSC = 31.2mA/cm2), while G5 achieves the highest PCE (37.0%) through balanced photovoltaic parameters. The results establish terminal acceptor engineering as a highly effective strategy for developing high-performance organic photovoltaic materials, with G7 and G5 representing prime targets for experimental validation.

Biodiversity is a term increasingly recognized in science, policy, and society, accompanied by a growing body. In this article, we focus on key concepts, debates, patterns, trends, and drivers related to biodiversity. We begin by reviewing the history of the term and its various dimensions and values. Next, we explore what is known and unknown about global biodiversity patterns and examine changes from early human history to the present, including extinction rates and direct drivers of biodiversity change, while also highlighting some lesser-known factors. Lastly, we consider possible ways to stop the ongoing loss of life on earth and address the causes of global biodiversity loss, especially humanity's growing consuming footprint.

The present study reports the metabolic profiling and antimicrobial evaluation of Vitex negundo seed extract. UHPLC-QTOF-MS/MS analysis identified seventeen bioactive phytoconstituents, correlated with the observed antimicrobial and antifungal activities. Among them, isoorientin (-7.3 kcal mol ⁻ ¹), quercetin (-7.8 kcal mol ⁻ ¹), and orientin (-7.4 kcal mol ⁻ ¹) exhibited strong binding affinities towards Staph Gyrase B (24 kDa). Similarly, isoorientin (-8.1 kcal mol ⁻ ¹), quercetin (-8.4 kcal mol ⁻ ¹), and orientin (-8.3 kcal mol ⁻ ¹) displayed significant interactions with secreted aspartic proteinase (SAP2) enzyme, confirming their antimicrobial potential. The aqueous-methanolic seed extract demonstrated notable inhibitory activity against Staphylococcus aureus (26.4 ± 0.3 mm; 44.08% inhibition) and Candida albicans (25.7 ± 0.4 mm; 29.73% inhibition). Density functional theory (DFT) calculations at B3LYP/6-31G level were used to optimize the ground state geometries of the identified phytochemicals and analyze their frontier molecular orbitals (FMOs) and global reactivity descriptors. Time-dependent DFT (TDDFT) calculations at the B3LYP/6-311G level (solvent: DMSO) further explored their biological relevance and nonlinear optical (NLO) properties, including ionization potential (IP), molecular electrostatic potential (MEP), and HOMO-LUMO energy gaps. These quantum chemical parameters provided mechanistic insights into the antimicrobial potential of the identified constituents. Molecular docking simulations further confirmed strong geometric complementarity and favorable binding affinities, highlighting the Vitex negundo seed extract as a promising source of a novel medicinal agent with previously unreported antifungal and antibacterial activities.

The rapid proliferation of Consumer-Centric Industrial Internet-of-Things (CCIIoT) ecosystems has substantially expanded the attack surface for diverse cyber threats. Conventional intrusion detection systems (IDS) primarily rely on signature-based techniques, which exhibit limited effectiveness against zero-day and evolving attack patterns. To address these limitations, this study proposes a deep learning–driven IDS framework that concurrently integrates multiple modality-specific models. The proposed architecture employs a Gated Recurrent Unit (GRU) for host system log analysis, a Long Short-Term Memory (LSTM) network for network flow modeling, a 1D Transformer for packet-level traffic inspection, and a fine-tuned TinyBERT model for phishing email detection. The probabilistic outputs of these heterogeneous models are combined through a learnable adaptive fusion mechanism, enabling confidence-aware decision aggregation across modalities. Extensive experiments conducted on the UNSW-NB15, CIC-IDS2018, CTDAPD, and phishing email datasets demonstrate that the proposed framework outperforms conventional IDS approaches, achieving improved accuracy, F1-score, and ROC-AUC while significantly reducing false positive rates. The framework is explicitly designed as edge-aware through lightweight architectures edge-aware and late-fusion strategies, while detailed deployment benchmarking is reserved for future work.