Factors Affecting Cotton Production in Pakistan:Empirical Evidence from Multan District

This paper attempts to examine the factors affecting cotton production in Multan region using primary source of data. A sample of 60 small farmers, 25 medium and 15 large farmers was randomly selected from two Tehsils namely Multan and Shujabad of district Multan. The Cobb-Douglas Production Function is employed to assess the effects of various inputs like cultivation, seed and sowing, irrigation, fertilizer, plant protection, inter-culturing / hoeing and labour cost on cotton yield. The results depicted that seed, fertilizer and irrigation were found scarce commodity for all category of farmers in district Multan. The Cobb-Douglas Production Function results revealed that the coefficients for cultivation (0.113) and seed (0.103) were found statistically significant at 1 percent level. The Cost-Benefit Ratio for the large farmers was found higher (1.41) than that of small (1.22) and medium (1.24) farmers. There is a dire need to ensure the availability of these scarce inputs by both public and private sectors as these inputs were major requirement of the cotton crop.Cotton; Cobb- Douglas Production Function; Cost Benefit Ratio; Marginal Value Product; Allocate Efficiency of Critical Inputs; Multan District; Pakistan

Zero-tillage Technology and Farm Profits: A Case Study of Wheat Growers in the Rice Zone of Punjab

This study presents the results from a field survey of the wheat growers in the rice-wheat zone of Punjab. The late maturing basmati rice varieties and the post paddy-harvest conventional tillage practices to prepare seedbed for wheat sowing often result in delayed planting of the crop. The late sowing is a major factor responsible for low wheat yields obtained by the farmers of the area. Introduction of the new zero-tillage seed drill in the area during early 1980s made it possible to sow wheat in freshly harvested untilled paddy fields utilizing residual moister. Presently, more than eighty thousand hectares of wheat are sown with zero-tillage drill technology. The partial budget analysis showed that zero-tillage is more profitable than conventional wheat sowing methods of ‘wadwatter’ or ‘rauni’. The new technology saves tillage and irrigation costs, results in yield gains through a possible improvement in sowing time and enhanced fertilizer and water use efficiencies. The results showed that the zero-tillage adopters earn an extra income of 253 and 2278 rupees per acre of wheat over that earned from wheat sown with rauni and wadwattar methods respectively. The results of multiple regression analysis confirmed that the zero-tillage technology enhances water and fertilizer use efficiency. However, sufficient evidence was not present to prove any positive or adverse affect of the technology on the incidence of weeds in wheat crop. It is suggested that this aspect of zero-tillage technology be focused more in future research.wheat; Zero-tillage; technology; irrigated Punjab; rice-wheat zone; Pakistan

Upper Limb Movement Execution Classification using Electroencephalography for Brain Computer Interface

An accurate classification of upper limb movements using electroencephalography (EEG) signals is gaining significant importance in recent years due to the prevalence of brain-computer interfaces. The upper limbs in the human body are crucial since different skeletal segments combine to make a range of motion that helps us in our trivial daily tasks. Decoding EEG-based upper limb movements can be of great help to people with spinal cord injury (SCI) or other neuro-muscular diseases such as amyotrophic lateral sclerosis (ALS), primary lateral sclerosis, and periodic paralysis. This can manifest in a loss of sensory and motor function, which could make a person reliant on others to provide care in day-to-day activities. We can detect and classify upper limb movement activities, whether they be executed or imagined using an EEG-based brain-computer interface (BCI). Toward this goal, we focus our attention on decoding movement execution (ME) of the upper limb in this study. For this purpose, we utilize a publicly available EEG dataset that contains EEG signal recordings from fifteen subjects acquired using a 61-channel EEG device. We propose a method to classify four ME classes for different subjects using spectrograms of the EEG data through pre-trained deep learning (DL) models. Our proposed method of using EEG spectrograms for the classification of ME has shown significant results, where the highest average classification accuracy (for four ME classes) obtained is 87.36%, with one subject achieving the best classification accuracy of 97.03%

Moral Hazard, Monitoring and Punishment: Evidence from a Field Experiment

The existing literature establishes that there exists inefficiency in energy consumption in Pakistan. In particular, with regard to electricity consumption, the problem of moral hazard is prevalent in the public sector. In this study, we observe this aspect by focusing on the behaviour of consumers once they are held liable to monitoring with the associated punishment mechanism. By providing evidence from a field experiment, we make three conclusions. First, individuals respond to both the monetary and non-monetary punishments. Alternatively, with the introduction of punishments, they reduce moral hazard with respect to electricity consumption. Second, the habitual violators of rules reform their behaviour after they are made accountable for their actions. Third, if appropriate monitoring systems along with the associated punishment mechanism are introduced, we can have beneficial effects in terms of resolving the energy crisis on the aggregate level. JEL Classification: H83, D12, D00, D03, D04 Keywords: Moral Hazard, Monitoring, Punishment, Electricity Consumption, Public Secto

Quality and Audit Fees: Evidence from Pakistan

Audit quality has been in the limelight for researchers over the last two to three decades. Researchers have endeavored to find out the factors that impact the quality of audit conducted by the auditors. The recent financial crises and financial scandals have further enhanced the importance of this topic. Although it is an empirically established fact that auditor’s performance is impeded by a number of factors that curb its independence however sudden surge in the emoluments of auditors during the last decades has actuated the researchers to study audit quality in context of compensation fee paid to the auditors. The results of studies differ as some are of the view that audit quality improves with the payment of excess fee while the rest are of the opposite view. Unluckily, Pakistan has been less explored in this regard and not even a single study has addressed the issue of audit quality in Pakistan. This study has attempted to analyze audit quality in context of abnormal or extra fee paid to auditor. Audit conducted without independence of auditor is futile and results in impairment of audit quality. Independence of auditor is usually curbed by extra fee paid to him, and auditor in fear of losing a lucrative fee does not report the misrepresentations of financial statements in his audit report. This study uses discretionary accruals as surrogate of audit quality which are computed by Cross-sectional Modified Jones Model (1995). The results are fortunately good for Pakistan and study has observed that auditors in Pakistan do not compromise on their standards and honesty when paid extra fee. In Pakistan, the quality of audit is not impaired when auditors are paid extra fee and the auditors work with diligence and exert extra effort to improve the audit quality. Therefore, the assertion that audit quality is impaired when high fee is paid to auditors does not hold well in Pakistan. Keywords: Audit fee, Audit Qualit

An effective data-collection scheme with AUV path planning in underwater wireless sensor networks

Data collection in underwater wireless sensor networks (UWSNs) using autonomous underwater vehicles (AUVs) is a more robust solution than traditional approaches, instead of transmitting data from each node to a destination node. However, the design of delay-aware and energy-efficient path planning for AUVs is one of the most crucial problems in collecting data for UWSNs. To reduce network delay and increase network lifetime, we proposed a novel reliable AUV-based data-collection routing protocol for UWSNs. The proposed protocol employs a route planning mechanism to collect data using AUVs. The sink node directs AUVs for data collection from sensor nodes to reduce energy consumption. First, sensor nodes are organized into clusters for better scalability, and then, these clusters are arranged into groups to assign an AUV to each group. Second, the traveling path for each AUV is crafted based on the Markov decision process (MDP) for the reliable collection of data. The simulation results affirm the effectiveness and efficiency of the proposed technique in terms of throughput, energy efficiency, delay, and reliability. © 2022 Wahab Khan et al

Frequency and Pattern of Early Complications after Endoscopic Third Ventriculostomy in Obstructive Hydrocephalus

Objective:  To determine the frequency, pattern and outcome of early complications after endoscopic third ventriculostomy (ETV) in Obstructive hydrocephalus. Material and Methods:  The study included 160 patients from Neurosurgery department, Lady Reading Hospital Peshawar and private clinics over a period of twelve months. After performing ETV under general anesthesia by a single expert neurosurgeon, the patients were followed up for seven days post operatively for the CSF leak, wound infection, meningitis, seizures, bleeding and in hospital death. Results:  Eighty five percent of the patients had no untoward complications, while 15% showed complications including CSF leak (5%), wound infection (3%), meningitis (2%), seizures (2%), bleeding (2%) and in hospital death (1%). Conclusion:  Due to the less invasive nature, endoscopic third ventriculostomy is favored for treating obstructive hydrocephalus in select patient population as it is safe and have better outcomes

Personality Trait Recognition using ECG Spectrograms and Deep Learning

This paper presents an innovative approach to recognizing personality traits using deep learning (DL) methods applied to electrocardiogram (ECG) signals. Within the framework of detecting the big five personality traits model encompassing extra-version, neuroticism, agreeableness, conscientiousness, and openness, the research explores the potential of ECG-derived spectrograms as informative features. Optimal window sizes for spectrogram generation are determined, and a convolutional neural network (CNN), specifically Resnet-18, and visual transformer (ViT) are employed for feature extraction and personality trait classification. The study utilizes the publicly available ASCERTAIN dataset, which comprises various physiological signals, including ECG recordings, collected from 58 participants during the presentation of video stimuli categorized by valence and arousal levels. The outcomes of this study demonstrate noteworthy performance in personality trait classification, consistently achieving F1-scores exceeding 0.9 across different window sizes and personality traits. These results emphasize the viability of ECG signal spectrograms as a valuable modality for personality trait recognition, with Resnet-18 exhibiting effectiveness in discerning distinct personality traits

The Effects of Informational Framing on Charitable Pledges: Experimental Evidence from a Fund Raising Campaign

We designed a field experiment to test the direction of the impact of informational frame on charitable pledges. We solicited charitable pledges from 395 students during a campaign aimed at helping students through students at the School of Economics, Quaid-i-Azam University (QAU), Islamabad. The participants are randomly divided into 5 different treatments. In the Pledge Disclosed (PD) treatment, we provided information to students about the average size of pledge we received from participants in the Baseline (BL) treatment. Similarly, in the Need Disclosed (ND) treatment, we provided information about the total need of those who asked for assistantship. In the Pledge & Need Disclosed (P&ND) treatment, we informed the students about both the need as well as the pledge made by the students to meet that need. In All Disclosed (AD) treatment, we provided details about the need, pledges, the previous history of the project, and the pledge by Charity Australia International. The findings show that relative to BL treatment, charitable pledges decreased when participants were informed about the previous pledges and the total required need. However, charitable pledge increased when full information was provided to the participants. JEL Classification: D64 Keywords: Charitable Pledges, Philanthropy, Helping Students through Students, Field Experimen